Guild.ai

“The question I’m asking is: are we measuring work or value? An agent doing more work doesn’t necessarily mean the business is getting more value. Most organizations can tell you what they’re spending. Very few can tell you what they’re getting in return. That’s the gap I think the industry needs to close.” @jevering ICYMI, check out Guild CEO James Everyingham's tokenmaxxing convo with @LinearB_Inc's DevInterrupted, alongside @LaunchDarkly's @cetezadi and @TryArcade's @AlekzSalazar . devinterrupted.substack.com/p/whether-toke…

It's been a blast meeting up with the developer community around San Francisco this summer. There's so much we can do alone with AI... but at the end of the day, there's just no replacement for getting out there and building together. As for us, we'll be out building in public all year long. If you spot us, come say hi!

We're building a new category for AI infrastructure. And we need your help. Check out a couple of our open roles below or visit our careers page to join the Guild team in the fray. ⚔️ Demand Generation Lead: $140K – $220K + Bonus & Equity > lnkd.in/gxJ5rd4d ⚔️ AI Engineer, Production Agents: $140K – $320K + Bonus & Equity > lnkd.in/gWFSR32e Don't see a job that fits? View all our open roles here > lnkd.in/gFbXQi4w

@Microsoft is cutting costs by relying on its own models. What about you? You don't have your own frontier model to prioritize. How do you realistically control your AI costs at scale without sacrificing performance or flexibility? The answer for most enterprise teams isn't exclusivity -- it's a model-neutral infrastructure layer. When you can catalog, manage, run, and monitor your agents in a single surface, the conversation becomes less about cutting costs and more about optimizing them. Token costs aren't the enemy. Wasting them is. And prioritizing neutrality at scale is the best way to solve it. We're building for a model-agnostic future. We hope you are too. Learn more at guild.ai

AI Observability ≠ AI Governance One of the most costly misconceptions about AI observability is that it's synonymous with AI governance. But it isn't. The problem with AI observability isn’t that it’s unhelpful -- it’s that it’s retrospective. AI observability can give you traces, token counts, latency, and a record of what happened -- which is still valuable for sure -- but the best trace in the world won’t stop an issue from happening. Unlike observability, governance isn’t primarily concerned with identifying agent problems -- it's concerned with controlling those agents before problems arise. In other words, observability tells you what already happened. Governance determines what *can* happen. And it's both of these together that make it possible to understand and manage your agents at scale. Observability is a component of a strong governance strategy; but observability is not equal to a governance strategy. When it comes to operationalizing any enterprise solution, the application of a tool is just as important as the tool itself. Governance doesn’t work without visibility—but the power isn’t in what you see, it’s what you can respond to proactively. More about this topic here 👉 guild.ai/blog/agent-gov…

@jevering shares his thoughts about finding the right models for the right tasks--and where he sees the future of agents as infrastructure. Shoutout to @MTSlive and @gbrl_dick for the conversation.

We're excited to welcome Val Bays as Guild's Chief Design Officer. The future of AI isn't just about smarter models. It's about building products people trust. Welcome, Val. Read why she joined Guild: guild.ai/blog/news/why-…

Are you headed to @aiDotEngineer Worlds Fair? 6K+ attendees. 300 speakers. 100 AI labs on the expo floor. And one problem that's going to be top of mind everyone... Agent governance. If you're an enterprise leader asking how to govern agents effectively at scale, Guild's own Ben Oren and Corbett Waddingham will be onsite all week, and they would love to connect! DM Ben or Corbett on LinkedIn to grab a time 🗓️ Ben: linkedin.com/in/bforen/ Corbett: linkedin.com/in/waddingham/

Have you seen the new Guild Insights Dashboard? It's the first single view for your agents to understand at a glance how they consume resources, drive usage, and incur costs in real time. Check out this quick demo to find out how teams on Guild can: - See spend in dollars—to understand real financial impact, not just the token counts. - Trace costs to the source—to visualize spend by workspace, provider, model, and user. - Track spending by period — to measure and compare costs across a 7/30/90-day window. - And identify waste — to optimize token costs and reduce spend over time. Want to learn more? Check out our latest engineering blog: guild.ai/blog/product/i…

Every agent platform claims to make agents "governable"... but no two platforms are defining governance the same way. Some tools generate logs. Some send alerts. Some create dashboards you'll look at once and never open again. If we don't agree on the outcome, we won't agree on the criteria to evaluate it. Here are four criteria to consider: - Access and identity: which systems can an agent reach, with whose credentials, and how easily can that be changed or revoked? - Model flexibility: can you run the best model for each task (Claude, GPT, Gemini, open source) or are you locked into one provider's stack? - Cost control: can you cap your spend before an agent burns through your budget, or will you find out when the invoice arrives? - Runtime oversight: can you see what your agents are doing and act on it, or will the logs tell the story post-mortem. Want to read more? Check out our guide here: guild.ai/blog/ai-insigh…

Who owns agents when they fail? Some studies (like the recent report from @cloudsa) suggest that as few as 15% of organizations have near-to-full agent ownership. That means 85% of organizations are leveraging AI in production environments with little or no accountability. And we’re already starting to see the consequences. Rogue actions. Data leaks. Runaway token spend. All these problems trace back to a failure of ownership at the governance layer. In 2026, the race isn’t toward adoption. It’s toward ownership and accountability. Three questions every enterprise leader should be able to answer right now: 1. Who has visibility into what our agents are doing? 2. Who’s responsible for controlling them? 3. Who’s accountable when they fail? In 2026, the question of "how to build agents" is a foregone conclusion. The only question now is whether you’ve got the governance in place to support them at scale. Read more: guild.ai/blog/ai-insigh…

We're excited to welcome Ben Oren as Guild's Vice President of Sales. Over the years, he's helped build and scale go-to-market teams at @twilio, @Box, @JumpCloud, and Aampe... But what was most impressive about Ben wasn't his resume... it's how deeply he understood the AI governance problem -- and how convicted he was about solving it. Too much of the AI conversation today is focused on models. The conversations we're having are focused on something far more urgent... How do you actually operate AI inside a real company? Welcome aboard, Ben. Let's get to work! guild.ai/blog/news/why-…

Introducing the new Guild Insights Dashboard: the first single view to understand how your agents consume resources, drive usage, and incur costs in real time. With Insights, teams can: - See agent spend in dollars—to understand real financial impact, not just the token counts. - Trace costs to the source—to visualize spend by workspace, provider, model, and user. - Track spending by period — to measure and compare costs across a 7/30/90-day window. - And identify waste — to optimize token spend over time. And this is just the first step. As teams evolve from a handful of agents in testing to hundreds of agents in production, they need the same level of visibility, accountability, and governability as any other critical business system. That's the future we're building. The agent governance era starts now 👇 guild.ai/blog/news/guil…

There's a storm coming. As agent sprawl takes hold in the enterprise, it’s creating a perfect storm of increased complexity and decreased visibility that's poised to turn the current agent governance gap into an agent governance crisis. - Runaway token costs - Agent lifecycle management - Unmanaged security risks - And lack of organizational accountability In our latest article, we discuss four of the biggest agent governance challenges facing enterprise teams today and why better infrastructure is the antidote. guild.ai/blog/ai-insigh…