cd /news/artificial-intelligence/the-astrolabe · home topics artificial-intelligence article
[ARTICLE · art-47770] src=schrottner.at ↗ pub= topic=artificial-intelligence verified=true sentiment=· neutral

The Astrolabe

A technical analysis maps emerging AI tools—Tessl, Goose, Archestra, Kestra, Modelplane, RAG, and MCP—onto distinct layers of an agent loop architecture, revealing that while tools will change, the underlying layers remain stable. The piece argues that standardization has only occurred at the protocol layer (MCP, A2A, ACP), while governance, orchestration, and spec layers remain fragmented.

read4 min views1 publishedJul 4, 2026

An astrolabe doesn’t map every star. It gives you a way to find your position relative to the ones that hold still.

That’s the instrument I reach for when someone asks which AI tool they should be using. The honest answer is that the tools will be different in six months. The layers won’t.

I spent a week trying to make sense of a handful of names that kept showing up in the same conversations. Tessl. Goose. Archestra. Kestra. Modelplane. RAG, MCP, half a dozen others orbiting nearby. Each one has its own pitch, its own funding round, its own reason it’s the thing you should adopt next. Taken together they read like noise.

Taken apart, they sit on different floors of the same building. The agent loop again, the one I keep coming back to. Once you place each tool on a floor, the noise turns into a map.

Tessl sits left of the loop, at the intent layer. Turn a spec into something an agent runs against directly. This is the one tool on the list that pushes back instead of going along with it. A well-formed spec is not the same thing as a team that agrees on what the spec means. The Agora produces the second thing as a byproduct of producing the first. Tessl produces the first and assumes the second follows. It doesn’t, automatically. That’s the whole argument.

RAG and MCP are plumbing. Protocol, not position. They carry context into the loop and don’t take a side in any argument about who should be in the room when the spec gets written.

They’re also the one floor with an actual standard. MCP, A2A, ACP, all under Linux Foundation governance now, joint working groups, cross-protocol commitments. Passing data between systems is a solved problem with decades of precedent behind it, so it standardized almost on contact. Nothing else on this floor plan has that. Governance, orchestration, the harness, the spec layer: every vendor is still building its own version and calling it the obvious one. The standard showed up first at the floor that mattered least to this argument.

Goose is a harness. The scaffolding a raw model needs to become something that can actually run a loop. Claude Code is a competing harness. This is the part that executes, not the part that decides.

Archestra sits around the loop, not inside it. Registry, gateway, guardrails, cost tracking, observability. Its own pitch is roughly: stop wiring this together yourself. That’s the concrete version of an argument I’ve made before, about centralizing the agent loop as infrastructure so individual engineers stop each carrying their own version of it. Archestra is what that looks like once someone builds it as a product instead of a hope.

Kestra runs underneath, and it’s the odd one out. It predates the agent wave by years, an orchestrator in the Airflow lineage, now repositioning toward agentic workflows because that’s where the funding and the attention are. There’s a fair question buried in that: is bolting agents onto an existing pipeline the wrong end of the problem, or is orchestration the one layer where the existing pipeline genuinely carries over? I don’t think I’ve earned a clean answer to that one yet.

Modelplane sits at the bottom. GPU fleets, inference clusters, the layer where the model physically runs. It comes from the Crossplane world, and Crossplane’s own position is worth sitting with: that API-first infrastructure eliminates tribal knowledge. Publish a hardware class, declare a model, get an endpoint. Neither side needs to know the other’s job.

That’s true, and it’s worth being precise about where it’s true. Infrastructure-layer tribal knowledge can become an API. It should. Nobody needs a senior engineer’s intuition about which GPU pool has headroom this week. But product-intent understanding doesn’t reduce the same way. There’s no schema for why we’re building this feature and not the other one. You can declare a model. You can’t declare an agreement.

A year from now this list will have different names on it. That’s fine. It’s not the list that matters. What doesn’t move is the floor plan: something has to hold the spec, something has to carry context, something has to run the loop, something has to govern what it’s allowed to touch, something has to schedule it, something has to run the model underneath all of it. One of those floors has a standard. The rest are still every vendor for themselves.

Know which floor you’re standing on before you pick a tool for it. The team that agreed on the spec doesn’t change no matter which floor gets rebuilt this quarter.

── more in #artificial-intelligence 4 stories · sorted by recency
── more on @tessl 3 stories trending now
sponsored brought to you by zahid.host 4,200+ EU-deployed projects
reading about agents? ship yours in a single git push.

Run your AI side-project on zahid.host

EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.

$git push zahid main
Live at https://your-agent.zahid.host
Get free account → Pricing
from €0/mo · no card required
LIVE [news/the-astrolabe] indexed:0 read:4min 2026-07-04 ·