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technical.md

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1# Technical Research Pack
2
3Serves: adopt a technology area, design an integration approach, ground an architecture in current practice, assess feasibility before committing a roadmap.
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5**Dimensions (priority order — prune to the decision):**
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71. Landscape & maturity — dominant approaches, what's consolidating vs churning, what the current generation newly makes possible
82. Integration & interoperability — protocols, formats, auth patterns, where integrations actually hurt
93. Architecture patterns in practice — which named patterns dominate at what scale, and what the failures teach
104. Implementation reality — learning curve, tooling, operational burden, what teams say 6–12 months in
115. Ecosystem health — contributor/release vitality, backing durability, the five-year regret risk
13**Craft (the non-obvious):** read the retrospective threads, not the launch threads; favor accounts with production numbers over advocacy; before citing a pain point, check whether it was since fixed — an old complaint against a current version is a false claim; read repository metrics over time, never snapshots; issue trackers reveal the gap between docs and reality.
15**Freshness:** versions & compatibility ≤ 1 mo · ecosystem signals ≤ 6 mo · landscape ≤ 12 mo (AI-adjacent ≤ 3 mo) · patterns ≤ 2 yr.
17**Two-source classes:** version/compatibility claims; performance or scale numbers a recommendation rests on; claims that a technology or pattern failed — one post-mortem is an anecdote.
19**Feeds (bmm):** architecture spine (candidate paradigms, operational constraints) · brief (feasibility) · roadmap risk and estimates.

Technical Research Pack

Serves: adopt a technology area, design an integration approach, ground an architecture in current practice, assess feasibility before committing a roadmap.

Dimensions (priority order — prune to the decision):

  1. Landscape & maturity — dominant approaches, what's consolidating vs churning, what the current generation newly makes possible
  2. Integration & interoperability — protocols, formats, auth patterns, where integrations actually hurt
  3. Architecture patterns in practice — which named patterns dominate at what scale, and what the failures teach
  4. Implementation reality — learning curve, tooling, operational burden, what teams say 6–12 months in
  5. Ecosystem health — contributor/release vitality, backing durability, the five-year regret risk

Craft (the non-obvious): read the retrospective threads, not the launch threads; favor accounts with production numbers over advocacy; before citing a pain point, check whether it was since fixed — an old complaint against a current version is a false claim; read repository metrics over time, never snapshots; issue trackers reveal the gap between docs and reality.

Freshness: versions & compatibility ≤ 1 mo · ecosystem signals ≤ 6 mo · landscape ≤ 12 mo (AI-adjacent ≤ 3 mo) · patterns ≤ 2 yr.

Two-source classes: version/compatibility claims; performance or scale numbers a recommendation rests on; claims that a technology or pattern failed — one post-mortem is an anecdote.

Feeds (bmm): architecture spine (candidate paradigms, operational constraints) · brief (feasibility) · roadmap risk and estimates.

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