Tenex AI Review: Story-Point Engineering, Claude Rollouts, and Enterprise Fit

Velocity AI vs. Tenex is a comparison that comes up because both firms use similar language (embedded teams, fast delivery, outcome focus) while packaging their work quite differently. Tenex has a sharp positioning, a distinctive engineering billing model and real enterprise Claude work. Understanding what each model is built to deliver is the most important part of this evaluation.

This post is written by Velocity AI, so we have an obvious interest in how it reads. We have written it honestly, including where Tenex is the better fit. Updated October 2026 to reflect Tenex's current services, pricing model and published client work.

At a Glance

Team Size and Capacity

Tenex does not publish its headcount, and public estimates vary widely. What is visible is a firm that is growing: its careers page lists many on-site New York roles, including forward-deployed engineers with published salary ranges of $224K to $394K. In early interviews, its founders described taking only 12-month-plus contracts during the first year and focusing on mid-market enterprises whose CEOs have made AI a top-three company priority.

For most buyers, the useful question is not total headcount but allocation: how many people will work on your program, and will the same people stay through delivery? That question matters for any partner, including us. It matters most for Fortune 500 initiatives that need concurrent work across data infrastructure, integration, governance and change management.

Velocity AI draws on 100+ AI practitioners via CourtAvenue, so large programs get teams sized to their scope.

Story-Point Engineering: What It Is and When It Works

Tenex's AI Engineering service bills by story points that Tenex defines, delivered in two-week sprints. Each team includes a technical product manager and forward-deployed engineers. Compared with hourly billing, this ties spend to delivered scope and gives buyers a regular cadence to review progress.

The model works best when work can be broken into well-defined units: product features, internal tools, integrations with clear acceptance criteria. It is a less natural fit for work that is hard to size in advance, such as data infrastructure remediation, governance frameworks or multi-system integration with uncertain dependencies. Because Tenex defines the story points, buyers should agree up front on how points are estimated and how scope changes are handled. Some enterprise procurement teams will also want a cap or a budget envelope.

Velocity AI uses fixed-fee and milestone-based pricing, a structure enterprise procurement teams recognize, that gives budget certainty up front and applies to infrastructure-heavy programs as well as discrete builds.

Tenex's Claude Work and Brand

Tenex's strongest public proof is its Claude work. Anthropic's own customer story on Advantage Solutions names Tenex as the partner behind a rollout of Claude Enterprise, Claude Code and Cowork that grew from 150 users to thousands, with a projected 70,000+ labor hours saved per year. Tenex has also published a four-week Claude fluency sprint it ran for WebFX, with more than 300 attendees at the opening session. For a company that has standardized on Claude, that is directly relevant experience.

Tenex also benefits from founder visibility. Alex Lieberman co-founded Morning Brew, in which Insider Inc. bought a majority stake in 2020 at a reported valuation of about $75 million, and he maintains a large audience across newsletters, LinkedIn and podcasts. Tenex publishes a steady stream of technical writing, which makes its thinking easy to evaluate before a first call.

Where Tenex Genuinely Excels

We believe in honest advice. There are contexts where Tenex is the better fit:

Claude-standardized organizations. If your company has chosen Claude and wants a partner that has already run enterprise rollouts and fluency programs, Tenex has public proof that few firms can match.

Structured transformation audits. Tenex's 30/60/90-day transformation audits, ending in an AI adoption report, are a well-defined entry point for organizations still shaping their AI strategy.

Steady-cadence engineering. Story-point billing in two-week sprints suits teams that want a transparent delivery rhythm on well-defined engineering work.

CEO-led AI agendas. Tenex explicitly targets companies whose CEOs have made AI a top priority, and its founder-led positioning resonates with executives who want a peer-level partner.

How to Decide

The question with Tenex is not whether it is a good firm (it is) but whether your program fits its model.

If you have standardized on Claude, want a structured audit or an enablement program, or have well-defined engineering work that suits sprint-based story points, Tenex is worth a serious conversation.

If your initiative is an enterprise AI program that needs multi-model architecture, several workstreams staffed at once, regulated-industry compliance and fixed-fee procurement, Velocity AI is built for that.

We are willing to give you an honest assessment of whether your initiative matches our strengths. If it doesn't, we will say so.