Augusto Marietti

Agents need programmatic interfaces—such as APIs, MCP tools, command-line interfaces and protocols—instead of screens designed for human users. They present API connectivity as a basic requirement for the next phase of software.

In a post about Salesforce’s Headless360 announcement, Marietti describes CRM being rebuilt around APIs, MCP tools and CLI commands, then sums up the shift as “From Pixels to APIs.”

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They argue that an AI gateway can route requests by intent, matching routine tasks with cheaper models and reserving frontier models for complex reasoning. Routing choices can change the cost curve even as usage grows.

Marietti says log summarization should not require frontier-model prices, while complex reasoning can go to a more capable model.

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They describe this as a way for CFOs and technical teams to discuss AI spending without expecting finance leaders to interpret engineering metrics on their own.

Marietti’s post describes an “Operational Metrics Translation Table” and lists questions it can help answer: What is gross margin per AI request by customer segment?

• How exposed is the business to a model provider’s price change?
• Which internal teams drive AI spending?

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This is the place to start; it frames the rest as evidence for a single thesis.

After previously saying “Software was going Headless,” Marietti notes, Salesforce announced Headless360, which they describe as rebuilding 27 years of CRM as APIs, MCP tools and CLI commands, with no browser required and “built for agents, not humans.”

• They argue that the last 30 years of the internet were built for humans, while the next 30 are being built for machines that consume programmatic interfaces—MCP servers, CLIs and protocols—at far greater scale.
• The post closes on “From Pixels to APIs.
• AI connectivity is the new digital railroad,” and carries the hashtag #noaiwithoutapis.

For brands planning a campaign

Useful framing for an infrastructure or AI platform campaign aimed at technical buyers: it positions API connectivity, not model quality, as the scarce layer, and offers a vendor-neutral hook—a large incumbent’s platform change—rather than a product claim.

It is the most concrete treatment of cost mechanics in this set and a natural companion to the CFO-focused post below.

Opening with the premise that “your token usage is the LOWEST it will ever be,” Marietti challenges the assumption that tokens and cost move one-to-one.

• They argue semantic routing is the most effective lever on token spend: an AI gateway acts as a decision layer, mapping each request’s intent to an appropriate model.
• Simple, high-volume work such as log summarisation goes to fast, cheap models, while complex reasoning goes to frontier models.
• The stated outcome: token usage keeps climbing while the cost curve does not follow it.

For brands planning a campaign

Strong material for a keynote or long-form piece on token cost management. The argument is specific enough to build a session around and does not depend on naming a customer or competitor.

It is the clearest example here of the commercial problem Marietti is trying to solve and names the exact questions an enterprise buyer asks.

Marietti observes that C-suite involvement in technical platforms is now common because executives need to know where AI spend is going.

• They describe an “Operational Metrics Translation Table” built to connect technical and finance teams, on the premise that a CFO does not need p99 latency or token throughput explained but does need to know what those metrics mean for the P&L.
• They then list four questions an AI gateway can help answer: gross margin per AI request by customer segment; cost exposure if a major model provider reprices; margin already created through caching and routing; and which internal teams drive AI spend.

For brands planning a campaign

Directly usable for demand generation aimed at enterprise CFOs and platform owners: the four questions can become a checklist, webinar agenda or qualification framework for sales conversations.

It is the best item for understanding the personal narrative behind the business, useful when assessing whether a founder is a credible speaker.

Marietti describes opening a Kong office in Milan with more than 80 regional employees, partners and customers, framing it as a return to where the company began: “When Marco and I started in Milan it would have been near impossible to imagine this full-circle moment.”

• They say figures including the President of Italy encouraged the company to return and invest in local talent across engineering, sales, products and customer success, and that Milan is becoming a tech hub.
• The company chose July 20, which they call “Kong Day,” to honour the founding date, and is treating Milan as primary R&D in Europe.
• The post closes with a photo reference to the garage-era origin.

For brands planning a campaign

A founder-narrative angle rather than a product one, suitable for an event introduction, an origin segment in a keynote or a European-market story. It also signals a regional investment that a Europe-focused campaign could anchor to.

It provides the internal counterpart to the CFO-facing content and identifies who is in the executive conversation about AI costs.

Marietti welcomes Bruce Felt as Kong’s new CFO, describing Felt’s experience scaling enterprise companies past $1B and taking them to public markets three times. They frame growth with capital efficiency as the experience needed for the company’s momentum in “the new age of AI connectivity,” and sign off with “Onwards!”

For brands planning a campaign

Useful context for enterprise-readiness claims when a campaign needs to show that cost and capital discipline are executive priorities, not just marketing messages.

Read it alongside the Milan post to see how consistently the expansion message is repeated across markets and languages.

Marietti announces a Paris office opened after years of growth in France and Europe, bringing customer success, sales and professional services closer to customers. They acknowledge named colleagues and close with the French version of the company’s slogan, “Pas d’IA sans API,” followed by “EN AVANT!” and a note about a team football match.

For brands planning a campaign

Shows the slogan travels across languages, useful for a multilingual campaign or European event. It is a company-news post rather than a teaching piece, so treat it as background credibility, not a content hook.

Marietti previews the company’s LA Summit with four things they’re excited about: an executive forum where CFO Bruce Felt and engineering leadership discuss token cost management, controlling AI consumption, infrastructure spend, model margins and routing, and guardrails and semantic caching; dedicated conference tracks on token cost management, AI governance and APIs for the AI era; an audience they describe as engineers, architects and leaders building production AI systems rather than the “conference-circuit crowd”; and unannounced swag.

For brands planning a campaign

A ready-made agenda map for a co-hosted event or content series: its three tracks match the subjects named for the event, making event collaboration an obvious format to propose.

The post frames this as a shift from graphical interfaces to programmatic interfaces that agents can consume at much larger scale, using the line “From Pixels to APIs” and the hashtag #noaiwithoutapis.

For brands planning a campaign

For an API infrastructure or AI connectivity brief, this offers a strong opening thesis: the platform shift from human UIs to agent-ready APIs. A keynote or co-authored explainer can use major platform announcements as proof points, then connect the shift to API gateway and connectivity requirements for enterprise buyers.

Examples: Source 1

The post describes an “Operational Metrics Translation Table” that maps gateway operational metrics to financial equivalents, and lists four CFO-level questions: gross margin per AI request by customer segment, cost exposure if a major LLM provider reprices, margin already created through caching and routing, and which internal teams drive AI spend.

For brands planning a campaign

This is the clearest evidence for a campaign aimed at CFOs and technical buyers.

• A collaboration can build on the translation table and four questions to show how an AI gateway turns latency and throughput metrics into P&L language.
• The practical angle is stronger than generic “AI cost” messaging because it names specific finance questions a gateway can help answer.

Examples: Source 1

The post argues that semantic routing through an AI gateway can map request intent to the most appropriate model, sending simple, high-volume queries to fast, cheap models and complex reasoning to frontier models. The stated outcome is that token usage can keep climbing while the cost curve does not follow.

For brands planning a campaign

This supports a token cost management and semantic routing angle.

• A brand can explain model routing as a cost-control layer, with a concrete example such as avoiding frontier-model prices for log summarization.
• The mechanism gives technical buyers and finance stakeholders a shared basis for evaluation.

Examples: Source 1

The event includes dedicated tracks for Token Cost Management, AI Governance, and APIs for the AI era. They describe the audience as engineers, architects, and leaders building production AI systems rather than a conference-circuit crowd.

Event-led thought leadership that pairs finance and engineering voices around buyer problems rather than product features.

For brands planning a campaign

A brand can explore a summit, webinar, or event collaboration where finance and engineering co-present on AI gateway economics and governance. The post shows a format for bridging CFO concerns and technical implementation in one session.

Examples: Source 1

Marietti welcomes Bruce Felt as CFO, citing experience scaling enterprise companies to $1B+, taking companies public three times, and focusing on growth with capital efficiency for AI connectivity.

• Other posts announce the Paris office as a hub for customer success, sales, and professional services after European hypergrowth, and the Milan office opening with more than 80 regional Kongers, partners, and customers.
• The posts frame Milan as primary R&D in Europe and tie the date to Kong Day.

Milestone posts combine team recognition, local-language slogans, mission language, and event photos to mark company progress.

The posts announce company and event milestones. Ask for technical examples to assess their fit as the core topic case for an AI gateway campaign.

For brands planning a campaign

Marietti shows how hiring, office openings, and regional investment can become shareable company narratives.

• For a CFO-and-technical-buyer brief, the Bruce Felt hire supports finance-facing positioning, while the European expansion posts suggest possible regional event or employer-brand tie-ins.
• The core topic evidence remains token cost management and API-first AI connectivity.

Examples: Source 1 · Source 2 · Source 3

Examples include the “Scary thought” setup on token costs, the four questions a gateway can answer, the four Summit highlights, and the repeated #noaiwithoutapis and “Onwards” / “Avanti tutta” language. The posts often open with a tension or a moment, explain the infrastructure mechanism, and close with a practical list or call to action.

Pain-point hook, explanation of the infrastructure mechanism, then a compact list of questions, reasons, or actions.

For brands planning a campaign

This style works for sponsored posts, keynote clips, or co-authored explainers. A campaign can start with a platform-shift or CFO-cost tension and end with a named framework, such as the Operational Metrics Translation Table or a semantic routing model, giving the audience a concrete takeaway rather than a brand slogan.

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

In a post about the company's Milan office they say, "When Marco and I started in Milan it would have been near impossible to imagine this full-circle moment," and tie the office opening to "the moment the company was founded."

• The same post promotes Kong's AI gateway work and its Europe R&D plans.
• They speak for Kong elsewhere too: welcoming Bruce Felt as "our new CFO" and describing the Paris office as "our beautiful Paris office," and previewing Kong Summit sessions on token cost management and AI governance.

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The posts explain how to assess what an AI task is worth and when to stop spending, overlapping with Marietti's arguments about routing, token cost and AI gateway finance conversations.

Ford's posts center on a tokenomics decision framework for business and finance leaders, illustrated with a whiteboard-style value curve. Marietti's work focuses more on platforms: API-first software, AI gateway mechanics and translating gateway metrics for CFOs.

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Both use gateways to connect technical implementation with business decisions.

Cavalier explores workforce and learning, including human-AI task allocation, upskilling and AI-assisted video production. Marietti focuses more on API-first platform strategy, AI connectivity and enterprise cost controls.

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The format and takeaway are similar: explain a problem, break it into steps and point to operational actions.

Barwal focuses on mid-market process automation and ecommerce site speed, rather than AI gateways or platform strategy. Readers seeking API-first infrastructure and token cost governance will find more direct material from Marietti and Ford.

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Their two posts work through a four-number framework that is unusually usable in a finance meeting: business value as the ceiling the business sets before anyone spends, marginal value as the method for deciding when to stop, ROI as a report that looks best when you spend least, and net value as the result worth steering by.

• They make the point concrete with a task example — spend about $15 on a task and keep roughly $38, spend about $32 and keep about $48 — and are explicit that the answer sits task by task, not only on the company bill.
• They also widen the cost definition beyond tokens to vector databases, caching layers and orchestration, which most AI cost conversations skip.
• When the need is AI cost governance as a discipline, or a speaker who can hold a CFO's attention for a full session, Ford is the closer match on the argument itself.

Ford stays at the level of governance and measurement.

• They do not make the platform-architecture argument for software moving to headless, APIs and machine-consumable interfaces as the new connectivity layer, or an AI gateway as the decision layer that maps request intent to the right model.
• A sponsor selling an API gateway or AI connectivity product gets the strongest available finance argument, but not the product-category narrative, and would need a second voice for the engineering half of the room.
• Ford also writes from a vendor position, so buyers seeking a neutral platform comparison should ask how the analysis accounts for competing tools.

Examples: Source 1 · Source 2

Their AT&T write-up comes closest to the subject of AI gateway routing and cost trade-offs: they report the company processing about 45 billion tokens a day through an AI gateway that weighs accuracy, cost and latency and routes accordingly; open models saving 80–90% in some applications; managers holding token budgets as capital allocators; and the trade-off question of a 56% cost cut for a 2% quality drop.

• They then extend the discussion into what most infrastructure pitches omit — proprietary data, documented processes, and whether companies reinvest productivity gains in people.
• Their second post documents building a 48-second promo with an AI assistant in under an hour, naming exactly where the process broke down.
• It suits sponsors seeking someone who can show AI adoption in processes on camera or in a live build rather than just describe it.

The AT&T commentary is second-hand, covering a company Cavalier does not work for, so it offers less of the insider platform view a gateway vendor would want and no first-party cost data.

• Their strongest original asset is the production process, a different buyer problem from token cost governance and P&L translation: it answers “how do we make AI outputs faster” rather than “what should each AI request be worth”.
• They are comparatively weak on the CFO metrics layer that makes the case for finance-led AI cost governance specific.

Examples: Source 1 · Source 2

Their posts are decision shortlists a team can act on the same week: five internal processes worth automating first — lead qualification and routing, tier-1 support and order inquiries, cross-system data synchronisation, document verification and client onboarding, and real-time operational monitoring — with the manual and automated versions of each stated plainly.

• The eCommerce post takes the same approach to site performance, naming the three architecture issues they check first and the fixes for each, then giving a full-range example of moving from 3.8 seconds to under 1.2 seconds.
• Use Barwal for a practical automation or performance agenda aimed at a mid-market audience, or when the sponsor wants content that reads as implementable rather than strategic.

The content is tactical and list-shaped, with no enterprise cost-governance argument, API-first framing or CFO-facing translation layer.

• It answers “what should we automate first”, not “who owns our AI spend and how do we prove it paid off”.
• Sponsors buying executive positioning on gateways, routing or P&L exposure get a lower-altitude, implementation-focused voice and will need to supply the financial narrative themselves.

Examples: Source 1 · Source 2