Add ADR 0006: Project positioning as local agent infrastructure

Records the strategic positioning decision that Kakeya is
'local agent infrastructure for Mac', not a generic chat-acceleration
engine. Pure documentation, no code change.

Context
-------
Through v0.1.0 and v0.2.0 the project's external framing has been
chat-acceleration via DLM speculative decoding. A series of comparison
analyses (vs llama.cpp, mlx_lm, NVIDIA Nemotron self-spec) revealed
that Kakeya's design choices map cleanly to the requirements of local
agentic applications, but were never explicitly justified in that
frame. This ADR makes the agentic positioning explicit so future
release framing, integration documentation, benchmarking, and
prioritization decisions all flow from a coherent product story.

Decisions (§2)
--------------
2.1 Reframe v0.3+ release notes from 'chat acceleration' to
    'local agent infrastructure for Mac'. Technical detail
    (acceptance rate, alignment training, speculative speedup)
    becomes implementation evidence, not the headline.

2.2 Ship docs/integrations/ as v0.3.0 first-class deliverable:
    - langchain.md (ChatOpenAI base_url config)
    - crewai.md (multi-agent Crew)
    - autogen.md (AssistantAgent)
    - cursor-bridge.md (Cursor custom endpoint)
    - openwebui.md (drop-in URL config)
    Each ~50 lines, demonstrating multi-agent concurrent execution
    as the discriminator vs mlx_lm.server.

2.3 Add scripts/bench_agentic/ alongside existing chat benchmarks:
    - bench_long_session.py (>=4-hour growing context)
    - bench_multi_agent.py (3 concurrent agents)
    - bench_tool_call_reliability.py (1000 tool calls JSON parse rate)
    - bench_cancellation.py (mid-stream cancellation latency)
    - bench_persistent_memory.py (cross-session recall)
    Each with mlx_lm.server comparison numbers. Headline release
    claims must be backed by these benchmarks.

2.4 Establish 'what we are not' stance:
    - Not a llama.cpp replacement (model coverage)
    - Not a vLLM replacement (data-center serving)
    - Not a complete agent framework (substrate, not framework)
    - Not a chat product (single-prompt parity is fine)
    - Not a multi-model gateway (Qwen3-only is fine)

2.5 Re-prioritize v0.3 / v0.4 work under agentic lens. Technical
    decisions don't reverse; ordering and presentation change.
    Concrete reframing matrix in §2.5.

Alternatives considered (§3)
----------------------------
- Generic local LLM engine framing (rejected: llama.cpp dominates)
- Pure research engine framing (rejected: understates engineering)
- Chat speedup head-to-head with mlx_lm (rejected: no structural
  advantage on that axis)
- Combined agent framework + engine (rejected: overlap with
  LangChain/CrewAI/AutoGen/Cursor)
- Defer reframing to v0.4 (rejected: v0.3 framing decision is now)

Documentation updates
---------------------
- docs/adr/0006-local-agent-infrastructure-positioning.md (new ADR)
- docs/adr/README.md: index updated to include 0004 (in flight),
  0005 (planned), 0006 (Accepted) so readers see the planned shape
  of the decision tree.
- README.md: ADR badge updated to '0001 | 0002 | 0003 | 0006';
  ADR list at the bottom gets a one-paragraph entry for 0006.

Validation criteria (§5)
------------------------
1. v0.3.0 README and release notes lead with agentic-infrastructure
   framing.
2. At least three of the five integration examples ship with v0.3.0.
3. Agentic benchmark suite has at least bench_multi_agent.py and
   bench_long_session.py shipping with v0.3.0 + mlx_lm comparison.
4. Any post-v0.3.0 framing that contradicts §2.4 'what we are not'
   stance requires a follow-up ADR.

No code change. Full test suite still passes (sanity check: 93 tests
in 0.28s on the touched-area-adjacent surface).

Co-authored-by: FluffyAIcode <FluffyAIcode@users.noreply.github.com>

Author: cursoragent

README.md

@@ -3,7 +3,7 @@
 [![CI](https://github.com/FluffyAIcode/Kakeya-LLM-Inference-engine/actions/workflows/ci.yaml/badge.svg?branch=main)](https://github.com/FluffyAIcode/Kakeya-LLM-Inference-engine/actions/workflows/ci.yaml)
 [![Release](https://img.shields.io/badge/release-v0.1.0-blue)](https://github.com/FluffyAIcode/Kakeya-LLM-Inference-engine/releases/tag/v0.1.0)
 [![Platform](https://img.shields.io/badge/platform-Apple%20Silicon-lightgrey)](docs/local-inference-engine.md)
-[![ADRs](https://img.shields.io/badge/ADRs-0001%20%7C%200002-green)](docs/adr/)
+[![ADRs](https://img.shields.io/badge/ADRs-0001%20%7C%200002%20%7C%200003%20%7C%200006-green)](docs/adr/)
 
 Runs the speculative-decoding architecture designed in the prior product
 discussion using **real, public** weights:
@@ -468,3 +468,13 @@ explicitly rejected.
   and what intermediate step ships in v0.2 — `PooledVerifier`
   wrapper that makes pool memory accounting accurate without
   touching the model forward.
+- [ADR 0006 — Project positioning as local agent
+  infrastructure](docs/adr/0006-local-agent-infrastructure-positioning.md):
+  the strategic positioning decision that Kakeya is **local agent
+  infrastructure for Mac**, not a generic chat-acceleration engine.
+  Reframes v0.3+ release notes around multi-agent / long-session /
+  personalized usage, commits to shipping `docs/integrations/`
+  examples (LangChain / CrewAI / AutoGen / Cursor) and an agentic
+  benchmark suite (`scripts/bench_agentic/`), and explicitly declines
+  to compete with llama.cpp on chat speedup or with vLLM on
+  data-center serving.