# v0.94.0 Launch Copy

Bilingual launch posts for **Cognithor v0.94.0 — AutoGen Strategy Adoption** (released 2026-04-25).

Drop into Twitter / X, LinkedIn, Discord, Mastodon. Each has a strict-character version (Twitter) and a longer version (LinkedIn). Pick + post.

---

## Twitter / X

### DE (≤280 chars)

```
Cognithor v0.94.0 ist live.

AutoGen-Code auf Cognithor migrieren? Geht jetzt mit Search-and-Replace der Imports:

from cognithor.compat.autogen import AssistantAgent, RoundRobinGroupChat

EU-Hosting, lokale Modelle, PGE-Trinity-Sicherheitsmodell. Apache 2.0.

pip install cognithor==0.94.0
```

### EN (≤280 chars)

```
Cognithor v0.94.0 is live.

Migrating AutoGen code to Cognithor? Now a search-and-replace on imports:

from cognithor.compat.autogen import AssistantAgent, RoundRobinGroupChat

EU-hosted, local models, PGE-Trinity safety model. Apache 2.0.

pip install cognithor==0.94.0
```

---

## LinkedIn

### DE (long-form)

```
🚀 Cognithor v0.94.0 ist heute auf PyPI.

Microsoft hat AutoGen offiziell in den Maintenance-Modus versetzt und verweist auf das Microsoft Agent Framework als Nachfolger — mit hartem Migrations-Pfad von conversation-zentriert zu graph-basiert. Tausende Python-Teams stehen vor der Frage: bleibe ich bei AutoGen, gehe ich zu MAF, oder bleibe ich bei niemandem?

v0.94.0 positioniert Cognithor als drittes Lager: lock-in-freie EU-Alternative, lokal-first, Apache 2.0, mit PGE-Trinity-Sicherheitsmodell.

Was neu ist:

▸ cognithor.compat.autogen — Source-Compat-Shim für autogen-agentchat 0.7.5. AssistantAgent + RoundRobinGroupChat laufen 1:1 mit nur Import-Änderung. 17-Feld-Signatur-Parität verifiziert gegen das echte Paket.

▸ cognithor_bench — Reproduzierbares Multi-Agent-Benchmark-Scaffold mit Cognithor-Default + opt-in AutoGen-Adapter.

▸ examples/insurance-agent-pack — DACH-Versicherungs-Pre-Beratung als sichtbarer PGE-Demo. §34d-NEUTRAL, alle Fixtures synthetisch.

▸ ADR 0001 dokumentiert ehrlich, warum wir SelectorGroupChat / Swarm bewusst NICHT unterstützen: ein LLM ist keine tragfähige Sicherheitsgrenze.

Bewusst NICHT enthalten: ein "wir-sind-besser-als-X"-Narrativ. AutoGen war ein gutes Stück Ingenieursarbeit. MAF wird Azure-Enterprise gut bedienen. Cognithor adressiert die Gruppe, die EU-Souveränität + lokale Inferenz priorisiert.

pip install cognithor==0.94.0

Link in den Kommentaren.

#OpenSource #AI #LLM #DSGVO #Python
```

### EN (long-form)

```
🚀 Cognithor v0.94.0 just shipped to PyPI.

Microsoft has officially put AutoGen into maintenance mode and points to Microsoft Agent Framework as the successor — with a hard migration path from conversation-centric to graph-based. Thousands of Python teams are asking: stick with AutoGen, move to MAF, or look elsewhere?

v0.94.0 positions Cognithor as a third option: lock-in-free EU-alternative, local-first, Apache 2.0, with the PGE-Trinity safety model.

What's new:

▸ cognithor.compat.autogen — source-compat shim for autogen-agentchat 0.7.5. AssistantAgent + RoundRobinGroupChat run 1:1 with import-line changes only. 17-field signature parity verified against the real package.

▸ cognithor_bench — reproducible multi-agent benchmark scaffold with Cognithor-default + opt-in AutoGen adapter.

▸ examples/insurance-agent-pack — DACH insurance pre-advisory as a visible PGE-demo. §34d-NEUTRAL, all fixtures synthetic.

▸ ADR 0001 honestly documents why we deliberately do NOT support SelectorGroupChat / Swarm: an LLM is not a load-bearing security boundary.

Deliberately NOT in this release: a "we're better than X" narrative. AutoGen was solid engineering. MAF will serve Azure enterprise well. Cognithor addresses the segment that prioritizes EU sovereignty + local inference.

pip install cognithor==0.94.0

Link in comments.

#OpenSource #AI #LLM #GDPR #Python
```

---

## Discord (cognithor server, #announcements channel)

### DE

```
@everyone

**Cognithor v0.94.0 ist live** 🎉 — AutoGen Strategy Adoption.

🔁 `cognithor.compat.autogen` Source-Compat-Shim — search-and-replace deine AutoGen-Imports
📊 `cognithor_bench` Multi-Agent-Benchmark-Scaffold
🛡️ `examples/insurance-agent-pack` DACH-Versicherungs-Demo (§34d-NEUTRAL)
📐 ADR 0001 — warum kein SelectorGroupChat / Swarm
📋 Competitive-Analysis-Docs (AutoGen / MAF / LangGraph / CrewAI)

Install:
```
pip install cognithor==0.94.0
```

Migration-Guide: <https://github.com/Alex8791-cyber/cognithor/blob/main/src/cognithor/compat/autogen/README.md>
Release-Notes: <https://github.com/Alex8791-cyber/cognithor/releases/tag/v0.94.0>

Feedback in #feedback erwünscht.
```

### EN

```
@everyone

**Cognithor v0.94.0 is live** 🎉 — AutoGen Strategy Adoption.

🔁 `cognithor.compat.autogen` source-compat shim — search-and-replace your AutoGen imports
📊 `cognithor_bench` multi-agent benchmark scaffold
🛡️ `examples/insurance-agent-pack` DACH insurance demo (§34d-neutral)
📐 ADR 0001 — why no SelectorGroupChat / Swarm
📋 Competitive-analysis docs (AutoGen / MAF / LangGraph / CrewAI)

Install:
```
pip install cognithor==0.94.0
```

Migration guide: <https://github.com/Alex8791-cyber/cognithor/blob/main/src/cognithor/compat/autogen/README.md>
Release notes: <https://github.com/Alex8791-cyber/cognithor/releases/tag/v0.94.0>

Feedback in #feedback welcome.
```

---

## Mastodon (≤500 chars per toot, but threading is fine)

### DE thread (3 toots)

```
1/3 — Cognithor v0.94.0 ist live. 🚀

AutoGen wurde von Microsoft in den Maintenance-Modus geschickt; MAF ist der Nachfolger — mit hartem Migrations-Pfad. Cognithor positioniert sich als EU-Alternative mit PGE-Trinity-Sicherheitsmodell. Apache 2.0, lokale Inferenz first-class.

#Cognithor #LLM #OpenSource
```

```
2/3 — Was migriert: cognithor.compat.autogen ist ein Source-Compat-Shim für autogen-agentchat 0.7.5. Search-and-replace der Imports — fertig.

Was nicht migriert: SelectorGroupChat und Swarm. Bewusst. ADR 0001 erklärt warum: ein LLM ist keine tragfähige Sicherheitsgrenze.

#AutoGen #DSGVO
```

```
3/3 — pip install cognithor==0.94.0

Migration-Guide & Release-Notes:
🔗 https://github.com/Alex8791-cyber/cognithor/releases/tag/v0.94.0

Plus: cognithor_bench, insurance-agent-pack als sichtbarer PGE-Demo, Competitive-Analysis-Docs.

Apache 2.0. EU-Hosting. Kein Azure-Lock-in.
```

### EN thread (3 toots)

```
1/3 — Cognithor v0.94.0 is live. 🚀

AutoGen was put into maintenance mode by Microsoft; MAF is the successor — with a hard migration path. Cognithor positions itself as an EU-alternative with the PGE-Trinity safety model. Apache 2.0, local inference first-class.

#Cognithor #LLM #OpenSource
```

```
2/3 — What migrates: cognithor.compat.autogen is a source-compat shim for autogen-agentchat 0.7.5. Search-and-replace the imports — done.

What does NOT migrate: SelectorGroupChat and Swarm. Deliberately. ADR 0001 explains why: an LLM is not a load-bearing security boundary.

#AutoGen #GDPR
```

```
3/3 — pip install cognithor==0.94.0

Migration guide & release notes:
🔗 https://github.com/Alex8791-cyber/cognithor/releases/tag/v0.94.0

Plus: cognithor_bench, insurance-agent-pack as visible PGE-demo, competitive-analysis docs.

Apache 2.0. EU-hosted. No Azure lock-in.
```

---

## Reddit (r/LocalLLaMA, r/MachineLearning, r/Python)

### Title (EN)

```
Cognithor v0.94.0 — drop-in source-compat shim for autogen-agentchat after Microsoft's maintenance-mode switch
```

### Body

```
After Microsoft moved AutoGen into maintenance and started pushing users to MAF (graph-based, conversation→graph hard migration), I shipped a Cognithor release that gives AutoGen-AgentChat users a third option:

```
from cognithor.compat.autogen import AssistantAgent, RoundRobinGroupChat
```

What works as drop-in:
- AssistantAgent (17-field signature parity, verified against autogen-agentchat==0.7.5)
- RoundRobinGroupChat with composable terminations (& and | operators)
- TextMessage / HandoffMessage / ToolCallSummaryMessage / StructuredMessage
- OpenAIChatCompletionClient (wrapped onto Cognithor's 16-provider model router)

What's intentionally NOT supported:
- SelectorGroupChat (LLM-as-security-boundary doesn't survive prompt injection)
- Swarm (HandoffMessage freedom conflicts with PGE-Trinity)
- MagenticOneGroupChat (separate workstream)

ADR 0001 documents the rationale honestly. Cognithor uses Planner / Gatekeeper / Executor as enforced role separation; the shim respects that boundary.

License: Apache 2.0. No verbatim AutoGen code. NOTICE has the MIT attribution.

Repo: github.com/Alex8791-cyber/cognithor
PyPI: `pip install cognithor==0.94.0`
Migration guide: github.com/Alex8791-cyber/cognithor/blob/main/src/cognithor/compat/autogen/README.md

Happy to discuss the trade-offs in comments.
```

---

## Hacker News (Show HN)

### Title

```
Show HN: Cognithor v0.94.0 — source-compat shim for AutoGen post-maintenance-mode
```

### Body

```
Cognithor is an Apache-2.0 multi-agent framework with PGE-Trinity (Planner / Gatekeeper / Executor) as a forced role separation. After Microsoft put AutoGen into maintenance and started pushing users to MAF's graph-based model, I added a source-compat shim so AutoGen-AgentChat code can run on Cognithor by changing only import paths:

  from cognithor.compat.autogen import AssistantAgent, RoundRobinGroupChat

The shim mirrors autogen-agentchat 0.7.5's API surface. 17-field signature parity for AssistantAgent verified via inspect.signature against the actual installed package. RoundRobinGroupChat goes through a custom adapter that loops participants under the Gatekeeper.

Honest non-goals:
- SelectorGroupChat is not supported. An LLM picking the next speaker is not a load-bearing security boundary; prompt injection trivially bypasses it. ADR 0001 spells this out.
- MAF compatibility is not on the roadmap. Conversation→graph would mean replacing PGE-Trinity, which is the value prop.

Other v0.94.0 pieces:
- cognithor_bench: reproducible multi-agent benchmark scaffold (CLI: cognithor-bench)
- examples/insurance-agent-pack: DACH insurance pre-advisory reference pack with a visible ComplianceGatekeeper agent — concrete example of what the safety boundary looks like
- Competitive analysis docs comparing with AutoGen / MAF / LangGraph / CrewAI

Local-first by default (Ollama), 16 providers out of the box, EU-hosted releases. PyPI: cognithor==0.94.0.

Repo: github.com/Alex8791-cyber/cognithor
Release notes: github.com/Alex8791-cyber/cognithor/releases/tag/v0.94.0

Happy to talk about any of the design choices.
```

---

## Posting checklist

- [ ] Twitter / X — DE post on @cognithor (or main account)
- [ ] Twitter / X — EN post (separate tweet, same account)
- [ ] LinkedIn — DE post (Alexander's profile or company page)
- [ ] LinkedIn — EN post (separate post)
- [ ] Discord #announcements — DE
- [ ] Discord #announcements — EN
- [ ] Mastodon DE thread (3 toots)
- [ ] Mastodon EN thread (3 toots)
- [ ] Reddit r/LocalLLaMA (EN)
- [ ] Reddit r/Python (EN)
- [ ] Reddit r/MachineLearning (EN, requires verifiable affiliation)
- [ ] Hacker News (EN, Show HN)
- [ ] Optional: dev.to article (longer, technical deep-dive on the compat-shim design)
- [ ] Optional: cognithor.ai blog post (when site PR #2 is merged)

## Notes

- Twitter/X 280-char limit verified on each variant.
- Discord post uses backticks for the `pip install` line; if they don't render in your channel, fall back to plain.
- Reddit communities have stricter self-promo rules. r/Python permits release-notes posts; r/MachineLearning prefers research-paper-style. r/LocalLLaMA is the most receptive for this kind of release.
- Hacker News: post during US-morning hours (13:00–15:00 UTC) for best reach. Don't ask for upvotes — bounce risk.
- DON'T use the term "MAF killer" or any attack-framing. The release-notes deliberately avoid that.
