Edwin Trebels

Their standard examples are regulatory filings, clinical reports, product manuals and compliance records.

• They describe a compliance question whose answer existed in six document formats across three languages, with no system able to connect them.
• Trebels makes the point using other people's platforms, too: Dexory, which has scanned over a billion warehouse locations, says most physical AI projects die because the underlying data is bad; GKN Aerospace's automation technology director Andy Francis says the next factory gains will come from the terabytes of data its machines already throw off.
• Piers Linney's keynote claim that treating AI as an IT project is doomed, and his finding that only 30% of enquiries get answered properly because the data is not connected, get the same treatment.

In the TextDistil post, Trebels presents the knowledge-extraction pipeline from Prasad Yalamanchi's team at Lead Semantics, a company they call a partner, as a structural layer that makes a data lake searchable by meaning and gives compliance teams auditability they can defend.

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They report Jakob Freund at CamundaLocal London arguing for deterministic checkpoints inside otherwise autonomous processes, and object graphs as structured maps of what an agent touches, decides and connects to.

• Freund built his own agent with access to sales pipeline, travel and account data, and the first thing he added was a human approval gate.
• In Trebels's account, a live demo of an e-commerce returns agent that started issuing refunds was fixed not with better prompts but by separating concerns across purpose-built agents controlled by process models.
• They cite figures from Camunda's 2026 report: 84% of organisations cite business risk when IT lacks controls over AI in daily processes, 80% flag transparency gaps, and only 11% of agentic AI use cases reached production last year.
• The same reasoning underpins their commercial case for knowledge graphs, which they say give compliance teams auditability they can defend.

The returns agent that refunded items on stage, and Freund's own agent, which got a human approval gate before it was allowed to run.

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After a climate intelligence forum, they note that nobody asked for a knowledge graph or help with "AI readiness": one attendee had years of safety logs archived in a form nobody could search, while another was matching claims against documents whose street names had changed since they were written.

• Both described a problem they were already paying for or had failed to solve.
• Trebels advises selling into those problems rather than technology categories, applying the same test to their own business: "If your AI strategy depends on data your systems can't actually read, that's the problem we solve."

The two conversations Trebels had after the forum: nobody mentioned "knowledge graph" or "AI readiness," but both raised expensive, unsolved data problems.

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A procurement freeze, a vendor swap and a court limit are three different things.

• Beneath them, Trebels identifies two concerns: dependence on software governed by another country's law, and whether a state should let any vendor's system profile citizens before a crime exists.
• They cite Switzerland's defence agency rejecting Palantir because it concluded the risk was built into the architecture rather than fixable by contract, while noting the UK holds over £900M in Palantir contracts and Denmark has expanded its use into Greenland.
• Trebels concludes that where data lives and whether it can be audited are design choices, not fixed properties of the technology.

Trebels's close reading of the word "banned" separates a procurement freeze from a court ruling and a vendor swap, while showing that not everyone agrees with the direction of travel.

Trebels states plainly that they are an interested party because this is a problem they work on, which is consistent with their habit of disclosing commercial interest inside the post rather than leaving it to be inferred.

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At a Manufacturing Technology Centre robotics and automation event, they report many advanced implementations alongside repeated vendor grumbling about hesitation towards automation, delivered with a grim smile and the phrase "perhaps especially in the UK."

• The selling points, Trebels says, range from survival to filling the labour gap, but could be far more specific and effective.
• At a later physical AI day at the same centre, they record GKN Aerospace and Dexory making essentially the same argument back to them, and the launch of an MTC and Plug and Play partnership for advanced manufacturing.

Trebels's closing line from the robotics event: "The engineering is clearly ready. The growth story, the case each company makes for why it matters, often doesn't seem to keep pace yet."

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They describe a four-week TeamWorks programme with the University of Warwick and Monash University, in which a student team built an enterprise sales playbook for neuro-symbolic AI covering financial institutions, professional services, manufacturing, energy, logistics, public sector, defence, retail, e-commerce, consumer goods, pharmaceutical and life sciences, telecom, media, news and non-profits.

• Trebels says the team was seeded with research so it could spend its time finding gaps and validating rather than starting cold.
• They later brought in Rodrigo Corradi as a fractional sales enablement lead for three months to build that foundation: problem framing, repeatable messaging, objection handling and substantiation mapped to real processes.

Trebels's view of enablement as the bridge between sophisticated engineering and enterprise buying realities, and the verticals the student team worked through.

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From Elite Business Live, they report Julie Holmes naming "leading by proclamation"—telling teams to adopt AI without giving them time to learn it—and Dave Birss's finding that 93% of AI budget goes to technology against 7% to people, with 80% of adoption failures non-technical.

• From the climate intelligence forum, they report Andrew Ogden-Swift saying optimisers get switched off if operators do not accept them, and Chris Dean saying founders underestimate "the time it takes to get pilot to real."
• Trebels relates this to their own Toyota Kata training.

The phrase "leading by proclamation," which Trebels uses to describe the gap between an instruction to adopt AI and the time given to learn it.

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They cite The Conference Board's tracking of how many of the 100 largest US companies put "ESG" in their sustainability report title—around 40% in 2023, 25% in 2024 and roughly 6% on a partial-year count—and quote Andrew Ngigi of Klimani saying businesses were not asking for help to reduce emissions but to reduce waste and protect margins. Trebels concludes that the focus should be business-compatible, with environmental benefits to follow.

The report-title figures, paired with Ngigi's admission of how wrong the original assumption was, show how the language has shifted while the goal has not.

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Two posts document a CRM setup in which Lightfield updates the CRM automatically from email and meeting transcripts, and Kondo does the same for LinkedIn direct messages.

• A Granola notetaker integration came later.
• They frame the change as moving from sales that relies on heroic remembering to a system that remembers for you, and publish the build: a webhook trigger, JSON parsing, an agent request step and the exact prompt they use.
• They also note that a bulk delete feature they requested was built quickly and call the vendor's support top-notch.

The full prompt Trebels prints instructs the agent to create a contact and account if they do not exist, then add or update a note with the message data, making the post reproducible rather than aspirational.

Both posts carry referral codes. Trebels says they are not affiliated with the tools beyond those links, making the coverage disclosed self-interest rather than independent evaluation.

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Trebels introduces TextDistil, a Knowledge Extraction Pipeline developed by Prasad Yalamanchi and the AI engineering team at Lead Semantics, which they call "our partner."

• They write: "Most enterprise AI projects don't fail because of bad models.
• They fail because decades of institutional knowledge sits locked in documents no system can actually read."
• The examples are concrete: regulatory filings, clinical reports, product manuals, and compliance records.
• They say TextDistil builds semantic knowledge graphs on hypergraph architecture, turns unstructured knowledge into queryable and governed data, deploys on-prem, AWS, or Azure, and is LLM-agnostic.

For brands planning a campaign

For a knowledge graph or enterprise AI vendor, this post offers ready-made evidence for a campaign about data readiness, auditability, and regulated deployments. It also suggests a specific collaboration angle: Edwin Trebels can explain the semantic layer between raw documents and AI systems, often the missing piece in enterprise AI pitches.

Trebels reports from CamundaLocal London, where Jakob Freund spoke about blending deterministic and probabilistic workflows for AI agents, and about object graphs as structured, traceable maps of what an agent touches, decides, and connects to.

• Freund built his own AI agent with access to sales pipeline, travel, and account data, then added a human approval gate.
• A live demo showed an e-commerce AI agent handling returns and issuing refunds; the fix was not better prompts but separating concerns across purpose-built agents controlled by process models.
• Trebels quotes Camunda's 2026 report: 84% of organisations cite business risk when IT lacks controls over AI, 80% flag transparency gaps, and only 11% of agentic AI use cases made it to production last year.
• Their summary: "If you can't trace it, you can't trust it."

For brands planning a campaign

This is a strong anchor for a campaign about governance, auditability, and production-ready agentic AI. It also shows Trebels translating a process-automation vendor's keynote into a buyer-facing argument—useful for a webinar, guide, or advisory engagement.

Trebels unpacks the claim that Spain "banned" Palantir.

• Trebels distinguishes Spain telling state-owned firms not to sign new contracts, France's intelligence agency switching to a European alternative, and Germany's Constitutional Court ruling in 2023 that the legal basis for Palantir-powered police profiling was unconstitutional.
• Trebels frames two underlying concerns: digital sovereignty, because sensitive data running on software governed by another country's law creates dependency, and civil liberties, because profiling citizens before a crime exists raises a deeper question.
• Trebels notes Switzerland's defence agency rejected Palantir for architectural risk, while the UK holds over £900M in Palantir contracts and Denmark expanded use into Greenland.
• Trebels discloses that Trebels is an interested party because it is a problem Trebels works on, and argues: "sovereignty and capability often get framed as a trade-off, and they don't have to be."

For brands planning a campaign

This post can support a data sovereignty or European AI positioning campaign. Because Trebels has a stake in the issue, brands should present them not as a neutral commentator on Palantir but as a knowledgeable practitioner who can explain the design choices behind sovereignty and auditability.

At the Climate Intelligence Forum at the NatWest accelerator, Trebels records four takeaways.

• First, "Nobody sells sustainability anymore": The Conference Board tracked how many of the 100 largest US companies put "ESG" in their sustainability report title, dropping from around 40% in 2023 to 25% in 2024 and about 6% last year on a partial-year count.
• Andrew Ngigi of Klimani says: "How wrong we were.
• Businesses were not asking for help to reduce emissions.
• What they were asking for is help to reduce waste, to protect margins."
• Second, adoption fails on people: Andrew Ogden-Swift says operators will switch off optimizers if they do not accept them, and Chris Dean says founders underestimate "the time it takes to get pilot to real."
• Third, a founder mistake: Marianna Foerg says founders fail to agree who owns what early and then become joint owners who cannot commercialise.
• Fourth, "Nobody asks for a knowledge graph": one person had years of safety logs in a form nobody could search; another was matching claims against documents whose street names had changed.
• Trebels says both described problems they were already paying for or had not solved, rather than asking for a knowledge graph.

For brands planning a campaign

For climate, industrial, or enterprise AI campaigns, this offers a precise reframing: sell waste and margin protection, not sustainability language. It also shows how Trebels finds use cases in operational pain rather than technology categories.

At the MTC Manufacturing Technology Centre's "Robotics and Automation 2026" event, Trebels notes many advanced implementations, alongside repeated vendor grumblings about hesitation towards automation, often expressed with a grim smile as "perhaps especially in the UK."

• Selling points range from survival to filling the labour gap, but the unique selling points could be much more specific and effective.
• Trebels names Luke Woods of Leidos on graphs for mapping factories, Martin Smith of Wire Glide Zolutions on robot arm components, Gabor Zichy of E-Nano on robotics, sensing, edge computing, and AI turning physical operations into structured, measurable data, Loop Technology on confined-space robotics, Christopher Ewens of ICART on a cobot mounted on a mobile unit, Jack Cole on measurement tools for manufacturing and elite sports science, and Dr Kirsty Hewitson of the UK Atomic Energy Authority on robotics challenges.
• Their closing observation: "The engineering is clearly ready.
• The growth story, the case each company makes for why it matters, often doesn't seem to keep pace yet."

For brands planning a campaign

This is a useful example for manufacturing or robotics clients turning technical capability into a buying case. Trebels can translate engineering detail into commercial messaging—a clear partnership or advisory angle.

At the UK Mobility & Physical AI Day at the MTC in Coventry, Trebels reports that GKN Aerospace automation technology director Andy Francis argued the next gains in their factories will come from the data machines throw off.

• GKN is capturing terabytes of real-time data on the shop floor; the challenge is analysing it and feeding it back so manufacturing becomes more accurate, reliable, and consistent.
• Trebels also cites Dexory, which has scanned over a billion warehouse locations, saying most physical AI projects die because the underlying data is bad.
• The UK is backing this with a new MTC and Plug and Play partnership for advanced manufacturing and physical AI.

For brands planning a campaign

For aerospace, manufacturing, or industrial data platforms, this post offers proof points from named companies and a clear frame: value lies not in the hardware alone but in the data layer. It can support a campaign aimed at operations and quality leaders, not just innovation teams.

Trebels describes a four-week TeamWorks program at the University of Warwick, in collaboration with Monash University, where Team 20 delivered a final presentation on enterprise sales for neuro-symbolic AI.

• The team researched verticals including financial institutions, professional services, manufacturing, energy, logistics, public sector, defence, retail, e-commerce, consumer goods, pharmaceutical and life sciences, telecom, technology, software, media, news, and global non-profits.
• They say the team was "supercharged" with deep research from advanced AI search and LangOptima's knowledge graph memo repo, allowing them to focus on identifying gaps, diving deeper, and validation.
• They thank Tori Reynolds, Nicola Black, and the students by name.

For brands planning a campaign

This shows Trebels as a mentor and sales-enablement thinker, not just a commentator. For a vendor targeting regulated sectors, it suggests a collaboration around sales playbooks, vertical research, and teaching teams to explain knowledge graph value.

Trebels describes automating CRM updates through Lightfield CRM, which updates from emails and meeting transcripts, and Kondo, described as "Superhuman for LinkedIn DMs."

• They say the old weekly "sales meeting of shame" is gone because the CRM updates automatically.
• The workflow includes email and meeting notes updating the CRM, LinkedIn DMs no longer living in a separate platform, a daily automated email preparing them for meetings, and chat queries to the CRM for context.
• They also say they can ask the CRM to identify people similar to recent signers.
• Setup steps include creating a webhook workflow, parsing JSON, adding an agent request step, and using a prompt to create or update contacts and notes.
• They offer free trial codes for Lightfield and Kondo.

For brands planning a campaign

A good fit for a RevOps, sales-tool, or CRM integration partnership: Trebels documents a real workflow and a specific setup. Treat the referral codes as promotional placement, not independent proof that the tools outperform alternatives.

At Elite Business Live in London, Trebels reports Piers Linney saying businesses should stop asking what AI can make cheaper and start solving problems that were previously too expensive to solve at all.

• Linney says: "If you think AI is an IT project, you are doomed."
• Trebels notes that Linney points to data businesses already have, such as phone calls, CRM records, emails, and conversations, and says conversation is now the most important data in a business, even though much of it sits in untapped silos.
• Linney mystery-shops businesses and finds only 30% of enquiries get answered properly, not because the technology fails but because the data is not connected.
• Dave Birss of The Gen AI Academy says 80% of AI adoption failures are not technical but people and process, and 93% of AI budget goes to technology while 7% goes to people.
• Trebels says data readiness is not the whole answer but remains a fundamental pillar.

For brands planning a campaign

Useful for an AI adoption campaign that needs to move beyond model hype. The content supports messaging about data readiness, people, and process, and positions Trebels as someone who can connect executive keynote themes to practical enterprise AI deployment.

A post on the TextDistil knowledge-extraction pipeline describes decades of institutional knowledge locked in documents no system can read — regulatory filings, clinical reports, product manuals, compliance records — and concludes that the missing piece is a semantic layer, not another model.

• An event post quotes Piers Linney saying that treating AI as an IT project is doomed, and reports Dave Birss's figure that 80% of AI adoption failures stem from people and process rather than technical issues.
• A manufacturing post makes the same case from the shop floor: GKN Aerospace captures terabytes of real-time data, and the problem is now analysing it and feeding it back, while Dexory says most physical AI projects die because the underlying data is bad.

For brands planning a campaign

Useful for vendors selling data preparation, semantic layers, knowledge graphs or AI-readiness services. The argument meets buyers in operational language, not model benchmarks.

Examples: Source 1 · Source 2 · Source 3

At a Camunda event, they report Jakob Freund's case for blending deterministic and probabilistic workflows, using object graphs as structured maps of what an agent touches and decides, and placing a human approval gate as a deterministic checkpoint inside an otherwise autonomous workflow.

• They cite Camunda's 2026 figures: 84% of organisations cite business risk when IT lacks controls over AI in daily processes, and only 11% of agentic use cases reached production last year.
• A knowledge-graph post frames the same gap commercially, describing semantic knowledge graphs that give compliance teams defensible auditability.
• A sovereign-AI post closes with the claim that data location and auditability are design choices, not fixed properties of the technology.

Typically builds from a named talk or vendor statistic, then states the structural conclusion.

For brands planning a campaign

A strong fit for AI governance, observability and knowledge-graph vendors whose buyers need a defensible account of agent behaviour, particularly in regulated settings.

Examples: Source 1 · Source 2 · Source 3

It traces two underlying concerns: dependency on software governed by another country's law, and civil liberties around profiling citizens before a crime exists. It cites Switzerland's defence agency rejecting Palantir because the risk was built into the architecture rather than fixable by contract, notes the UK's contract position of over £900M and Denmark's expansion of use into Greenland, and argues that sovereignty and capability need not be a trade-off.

The post discloses Edwin Trebels's work on this problem, making the analysis's commercial interest clear.

For brands planning a campaign

Suits European sovereign cloud, data governance and regulated-AI campaigns that need a writer who distinguishes legal, procurement and technical claims rather than repeating a headline.

Examples: Source 1

It lists financial institutions, professional services, manufacturing, energy, logistics, public sector, defence, retail, e-commerce, consumer goods, pharmaceutical and life sciences, telecom, media and non-profits, with vertical landing pages for most.

• A later post introduces a fractional sales enablement leader engaged for three months to build problem framing, repeatable messaging, objection handling and workflow evidence for knowledge graphs and knowledge-graph-mediated translation.
• A manufacturing event post states the underlying critique: the engineering is ready, but the growth story and each company's case for why it matters often lag.

For brands planning a campaign

A fit for complex B2B platforms that need translational messaging for enterprise buyers rather than engineering-led content, and for vendor teams whose vertical research is thin.

Examples: Source 1 · Source 2 · Source 3

At a Manufacturing Technology Centre robotics and automation event, they report advanced implementations alongside vendor grumbling about hesitation towards automation — 'perhaps especially in the UK' — and cover start-ups working on robot arms, edge sensing, confined-space robotics and measurement tools.

• They argue that the start-ups' selling points could be expressed far more specifically.
• At a physical AI day at the same centre, they report GKN Aerospace's automation technology director saying the next gains come from data machines throw off, Dexory saying most physical AI projects die on bad data, and a new MTC and Plug and Play partnership for advanced manufacturing.

Firsthand notes name speakers and companies, quote them directly, and close with a judgement on how the sector talks about itself.

For brands planning a campaign

Relevant to industrial automation, robotics, manufacturing data and physical AI campaigns, especially those aimed at buyers who need a clearer value case than survival or filling a labour gap.

Examples: Source 1 · Source 2

A founder says the most underestimated factor is the time from pilot to real.

• At an Elite Business Live event, they report Julie Holmes on 'leading by proclamation' — telling teams to adopt AI without giving them time to learn it — and Dave Birss's split of 93% of AI budget going to technology against 7% to people.
• They agree, drawing on their own Toyota Kata training.
• The same post notes that when data is siloed, AI output is siloed too.

For brands planning a campaign

Useful for change management, training and adoption-focused campaigns that need operator-level evidence rather than vendor claims.

Examples: Source 1 · Source 2

It quotes an attendee saying businesses were not asking for help to reduce emissions but to reduce waste and protect margins.

• The advice drawn from this is to make the focus business-compatible and let environmental benefits follow.
• The same post carries a commercial point from an IP lawyer: founders fail to agree and record who owns what early, then end up unable to commercialise because they cannot agree.

For brands planning a campaign

Relevant to climate tech and ESG-adjacent vendors whose real buyers sit in operations, finance or legal rather than a sustainability team.

Examples: Source 1

The workflow also includes a Granola notetaker integration and a bulk delete feature added after they requested it.

• One post details the webhook trigger, JSON parsing and agent-request steps, including the exact prompt used.
• Both posts offer referral codes (three months free on Lightfield, two on Granola, one on Kondo).
• They frame the change as a shift from sales that relies on heroic remembering to a system that remembers for you.

Edwin Trebels says they are not affiliated with the tools beyond referral links. Brands should confirm the commercial relationship before treating this coverage as independent.

For brands planning a campaign

Suits SaaS tools with a genuine workflow story that can accept publicly disclosed referral links. The posts read as practitioner reports rather than paid placements.

Examples: Source 1 · Source 2

It summarises an investor panel on investment types and stages, investment readiness, funding stages, burn rate, team and due diligence.

• Their conclusion: it is worth building a business with those criteria in mind, whether or not outside investment is ever pursued.
• The post carries language-industry hashtags alongside growth and localisation.

For brands planning a campaign

A fit for founder programmes, regional business networks, funding bodies and professional services aimed at SMEs, with a clear summary of what investors actually look for.

Examples: Source 1

The format is consistent: firsthand notes, named speakers and companies, quoted claims and figures, one structural conclusion, and often a closing question or invitation to compare notes. Topics each month track where they have been, making the format predictable to plan around.

Field notes with named attribution, direct quotes and a clear conclusion; commercial interest is disclosed where it exists.

For brands planning a campaign

Brands can time coverage around an event or launch conversation, with a named, quoted write-up and a point of view they can respond to.

Examples: Source 1 · Source 2 · Source 3 · Source 4 · Source 5 · Source 6

One post calls them "a relatively new founder, building a company in today's environment," alongside the LangOptima integration work. Ask for their formal title and ownership structure.

Original disclosure

If you do this, you'll go from "old-school sales and marketing that relies on heroic remembering" to "modern sales and marketing where the system helps remember for you." … And watch this space as I navigate the business world as a relatively new founder, building a company in today's environment.

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A second post again describes Lead Semantics as "our partner" when connecting its knowledge-graph work to governance of AI agents. Ask how the partnership works commercially, including whether Trebels's business resells, integrates, or co-markets the product.

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They disclose the referral link and say the Lightfield team helped them configure the integration and shipped a bulk-delete feature they requested.

Original disclosure

I'm not affiliated with any of these tools, other than having some referral links if you want to try it out for yourself, for free: Lightfield — 3 months free with code LangOptima3.

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Mitchell Tan of Kondo is credited with helping with the integration.

Original disclosure

I'm not affiliated with any of these tools, other than having some referral links if you want to try it out for yourself, for free: … Kondo: Superhuman for LinkedIn DMs — 1 month free.

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The link is disclosed alongside the other tools.

Original disclosure

I'm not affiliated with any of these tools, other than having some referral links if you want to try it out for yourself, for free: … Granola — 2 months free.

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She writes about a single term triggering 81 EU fragrance-allergen requirements and why sequential translation systems miss regulatory relationships.

• This parallels Trebels's argument that a compliance answer can exist across six document formats and three languages with no system able to connect them.
• Both connect industry presentations to academic or standards-facing contexts and write for readers who need AI to be defensible in regulated settings.

Gene stays close to translation, localisation, and cosmetics or life-sciences regulation, often through a formal research frame such as peer review at Convergence 2026.

• Trebels ranges more widely across enterprise AI adoption, agent governance, sovereign-AI policy, manufacturing events, and sales enablement.
• Their posts are usually field notes from named events rather than research papers or regulatory deep dives.

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His Lightfield posts describe reconstructing CRM exports, transcripts, and event data into a chronological model so agents read actual relationship history instead of guessing.

• He argues the bottleneck is usually not the model or MCP.
• That overlaps with Trebels's repeated claim that the missing piece is a semantic layer, not another model.

Peiris writes as the founder of the CRM product itself, so his posts centre on company milestones, product architecture, and customer adoption.

• Trebels writes as an adviser and commentator covering other people's products and events.
• They document their own tool workflows with disclosed referral links and frame the data-readiness argument through knowledge graphs, translation, and regulated-industry examples.

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His posts describe customers building automations on top of Lightfield, using product-usage and trust-centre signals, and the fear GTM leaders feel when changing a CRM stack.

• Trebels's CRM posts cover automatic updates from email, meetings, and LinkedIn DMs.
• Both writers focus on the operator's experience of making the system remember for them.

Serna's material is mostly company- and community-facing: case studies from Lightfield customers, a Pavilion GTM talk, and arguments aimed at sales leaders considering a change.

• Trebels covers a wider range of subjects, including digital sovereignty, manufacturing robotics, climate-tech messaging, and enterprise sales enablement.
• Their tool posts include referral codes and a full setup prompt rather than a product case study.

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Their post on the July 31, 2026 fragrance-allergen rule walks through a single term expanding into 81 individual declaration requirements across 27 member states.

• It explains that sequential translation systems render "linalool" correctly but cannot query concentration thresholds by product type or jurisdiction.
• That makes the same compliance-auditability argument a knowledge-graph vendor needs, anchored in a concrete regulation and date.
• They also make the case to two audiences: enterprise localization practitioners at the TAUS EU Localization Championship in Rome, and academic peer reviewers at Convergence 2026 at the University of Surrey, where a co-authored paper with Prof.
• Vilelmini Sosoni sits in a track on LLMs supporting multilingual communication.
• Choose them when buyers want to see the approach withstand scrutiny from regulatory affairs and research reviewers, and the target vertical is cosmetics, life sciences or another regulated sector where naming and declaration rules drive the purchase.

The posts stay inside translation, localization and regulatory compliance.

• Edwin Trebels’s posts do not cover sales-enablement programmes, vertical sales playbooks, mentoring a student team through buyer research, or rewriting a vendor’s commercial messaging—the work that would make them useful for a go-to-market campaign.
• If the vendor needs someone to build the sales narrative, handle objections with a sales team, or produce vertical landing-page copy, the posts do not show that work.
• They are the stronger choice for a compliance-credibility campaign and the weaker one for a commercial-narrative campaign.

Examples: Source 1 · Source 2

The Series A announcement describes creating Lightfield as a world model of a business, with $47M led by Andreessen Horowitz, more than 5,000 companies signed up since November, and the argument that Salesforce-era records are the wrong substrate for agentic work because the underlying data is incomplete and lacks structure.

• A second post details the mechanics: schema rewritten programmatically through APIs, migrations running in a persistent Python sandbox, a chronological timeline per customer to encode causality, and the claim that MCP access is not understanding.
• Choose them when the campaign goal is category education and product credibility with GTM and SaaS buyers, and the vendor benefits from an operator who can answer technical architecture questions in public rather than repeat positioning.

Edwin Trebels is the principal of a product in the same territory, so they are not an independent voice; their posts advocate for their own approach and would read as co-marketing rather than outside assessment.

• The posts frame the problem around high-growth companies, funnel diagnosis and legacy CRM replacement, not compliance buyers’ auditability or jurisdiction-specific requirements.
• For an advisor to test a vendor’s traceability claims alongside compliance buyers, ask for an independent voice with a track record of making that case.

Examples: Source 1 · Source 2

A post describing a customer conversation gives specific, checkable details: accounts and research triggered by app installs, trust-centre visits used as an intent signal, product usage data from PostHog modelled in the CRM, about thirty automations running, and a sign-up flow that started as a fifty-block Zapier tree and was rebuilt in under a day.

• A second post reports asking 100 GTM leaders on Salesforce or HubSpot whether they loved their CRM and getting zero hands, then identifies fear of recommending something new and retraining a team as the dominant reaction.
• Choose them when the vendor wants field-level stories about what customers actually do with the product, or a speaker who can open a conference session on why adoption stalls.
• That maps directly to a moderated customer-interview series or an adoption-focused event format.

The posts are closely tied to the product Edwin Trebels works with, so the same independence limit applies: they promote a platform and would read as partner advocacy.

• The subject matter is GTM practice and CRM adoption, not regulated-industry deployment.
• For a financial-services or pharma campaign, ask for examples of regulatory framing, traceability, auditability or jurisdiction-specific compliance; these posts do not make that case.

Examples: Source 1 · Source 2