# Ori Shimon

Ori Shimon builds AI-assisted tools and processes for go-to-market and revenue operations teams, including internal pipeline software, HubSpot audits and process changes.

- Profile: https://b2binfluencer.marketing/creators/ori-shimon/
- LinkedIn: https://www.linkedin.com/in/orishimon
- LinkedIn followers: 3,476
- Topics: artificial-intelligence, revenue-operations, pipeline-management
- Based on 12 dated posts, latest 2026-10-08

## Summary

Ori Shimon is most useful for practical RevOps and GTM engineering work, HubSpot audits and AI-assisted tool builds.

- Best for: A B2B SaaS company wanting short RevOps work to cut HubSpot spend and surface pipeline problems.
- Not for: A paid LinkedIn sponsorship seeking guaranteed reach or documented campaign performance metrics.
- Check first: Confirm sponsorship terms, audience analytics, migration proof, and recent engagement results first.

### Takeaways

- Build a thin layer over existing tools instead of buying another platform.
- They reported a 56% lower HubSpot renewal after comparing the contract with actual usage.
- Give an AI agent CRM write access only behind staged checks and human approval.

## Main ideas

- **Build a thin layer over the tools you already own instead of buying another platform**: Ori Shimon argues that the best GTM software their team uses is not sold by any vendor. The team knows its own bottlenecks better than an outside vendor can, and current AI makes it practical to build a layer over existing systems without reinventing the wheel or getting locked into one provider. That layer sits over the CRM, call recordings and enrichment tools like AmpleMarket, bringing them together in one place.
- **A fix is not shipped until something checks the behaviour in production**: Ori Shimon separates writing a fix from confirming it. Pushing a change moves an issue to a verifying state, not closed. Verification drives a real browser against production and replays the scenario. Uncertainty counts as failure: if the check crashes or cannot tell, the answer is unknown, not fixed. A tool that reports success it did not observe is worse than no check at all.
- **Renewal savings come from cutting the lines you do not use, not from asking for a discount**: Ori Shimon argues that companies overpay on software not because vendors refuse to discount, but because nobody has the hours to compare the contract with actual usage. The method: read every contract line for cost, discount and quiet renewal terms; pull real usage from the API; compare the two; then take a list of lines to remove into the renewal. That turns negotiation from a request into a correction.
- **Give an AI agent write access to the CRM only behind staged checks and human approval**: Ori Shimon is enthusiastic about pointing an AI coding agent at HubSpot to map the pipeline, audit workflows and make bulk changes across thousands of records through plain conversation, cutting work that took days to about 30 minutes. The counterweight is a fixed rule set: start read-only, verify the counts, build the change switched off, then approve it. Speed and safety are compatible if the sequence is enforced.

## Work to read

- [Building a GTM platform on top of existing tools](https://www.linkedin.com/posts/orishimon_revops-gtmengineering-gtmops-activity-7487984271811604480-acGH)
- [Comparing a HubSpot contract with actual usage to cut renewal costs](https://www.linkedin.com/posts/orishimon_revops-gtmops-saasspend-activity-7497766234348961792-VTY7)
- [How Ori Shimon verifies an AI-assisted fix in production](https://www.linkedin.com/posts/orishimon_gtmops-claudecode-lovable-activity-7512970109980655616-PLRN)
- [Running HubSpot through an AI coding agent with human oversight](https://www.linkedin.com/posts/orishimon_gtmops-revops-claudecode-activity-7478088778897756160-0WAw)
- [Asking RevOps and GTM Ops whether they replaced HubSpot](https://www.linkedin.com/posts/orishimon_revops-gtm-ops-this-question-is-for-you-activity-7485076533414490112-n7so)

## Brand relationships

- **HubSpot** (mention)
- **Claude Code (Anthropic)** (mention)
- **Lovable** (mention)
- **AmpleMarket** (mention)

## Partnerships

Across five posts spanning July to October 2026, Ori Shimon names HubSpot, AmpleMarket, Claude Code and Lovable as software they use or evaluate in GTM and RevOps operations, not as disclosed paid partnerships. The posts publish no rate card, package, sponsored-format description or inquiry route. Brands should approach them directly to negotiate an engagement, likely focused on GTM operations, RevOps tooling, or AI-assisted build or audit work. Ask about sponsorship availability and terms.

## Alternatives

- Sergey Danishevskiy: Choose Sergey Danishevskiy when the buyer has not settled the build-or-buy question and needs to decide before operations work begins. The work models the three-year total cost of owning HubSpot versus building a custom CRM across three B2B SaaS scenarios, assuming AI-assisted development: an 8-seat, $1M ARR company at $61K against $225K; 45 seats and $15M ARR at $480K against $1.85M; and 250 seats and $100M ARR at $2.8M against $6M. The same material lays out what estimates must include once a prototype works: migrating real data, fixing permissions, maintaining email, calendar, billing, and product integrations, making reporting trustworthy, and ensuring someone other than the person who prompted the system can run it. A second post offers a five-point screen for RevOps partners: whether they diagnose before quoting, build rather than advise, plan for their own exit, cover the full revenue loop from marketing handoff to retention, and tie accountability to outcomes rather than hours. This is useful when a buyer is choosing a partner or defending a budget case to a board—not when HubSpot is already staying and the buyer wants to cut the bill.
- Chris Tveter: Choose Chris Tveter when the buyer has decided to stay on HubSpot and needs to get its native AI features switched on and adopted by reps. The material walks through the free HubSpot Sales Plugin for Claude skill by skill, with a recommended use for each: call prep before a meeting, a daily brief as the first task of the morning, logging a call in plain language right after hanging up, drafting a recap email from deal context, a pipeline pulse before the weekly review, contact lookup, contact import from a CSV or pasted list, and a catch-all for field updates and CRM questions. It also flags a safeguard: Claude shows the proposed change before writing to the account. A second post covers HubSpot Deal Progression in public beta: CRM updates suggested after each call, email, or meeting; a next best action; a drafted follow-up; a new Catch-Up tab; methodology configuration for MEDDIC, BANT, or SPICED; branded buyer deal plans; and a re-engagement prompt after 14 days of silence, along with the admin switches most teams miss. This is a good fit when the gap is rep adoption of tools the company already pays for.
- Orlando G.: Choose Orlando G. when the buyer’s operations problem sits inside a specific team process, not in the contract. The two posts cover repeatable process builds: using HubSpot Breeze to draft a discovery-call playbook framework, choosing among the generated options, correcting the answer-type setting HubSpot tends to default wrong, and attaching the playbook to the contact record so each question and answer lands on the timeline for whoever works the deal next. The second routes a shared support inbox into a HubSpot ticket queue, lets AI handle the first pass from the knowledge base, and hands off to a human with an assigned owner who must read the chat log before replying. This suits a buyer whose support email lands in one person’s inbox or whose reps conduct inconsistent discovery calls, and who wants to fix those processes with tools already in place.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/