Roadmap

Last verified against the code: 2026-11-14 (0.10.1)

From one agent's memory to the commons. Each phase has a measurement that says whether it worked (paper §7).

North star

The relay between models, and, for the memory that runs overnight, proven by what agents do. The product a person uses is the handoff: one project, what was done, what they corrected, what was deployed. Neverest is also an advance on the memory if an agent with it hands work back less and repeats fewer corrections than with no memory or with normal memory, on frontier models and in real use, if a lesson can end up in the model itself, and if one person's lesson helps another's agent. Those are goals A1–A9 (GOALS.md), each with a target fixed in advance. neverest goals checks every one from the evidence; nothing on this page is marked done from memory. A relay that is not measured is not yet one of them.

The program, in milestones

Milestone Goals What it takes Who State
M1. Controlled evidence (0.7.0) A1 neverest experiment on three model families agent done (A1 met)
M2. Mechanism, tools, a first compiled memory (0.8.0) A2, A3, A8 experiment mechanism, experiment loop, scripts/adapter.py, neverest goals agent done: A2, A3, A10 met; A8 not met (7B in 0.8.1: one short; contrast pairs next)
M3. Frontier models A4 the same commands against Claude, GPT or Gemini: one API key on the Linux box (NEVEREST_LLM_KEY) owner: the key; agent: the runs needs the owner
M4. Real use, held out A5, A6 living with the hooks until each arm has 20 primes; neverest measure weekly owner: daily work; agent: weekly check collecting
M5. Two machines, then the commons A9 neverest share invite on the Linux box (in the owner's terminal), the line pasted on the Mac; then commons-wide states (PROTOCOL §3) owner: one paste needs the owner
M6. Memory in the weights, nightly A8 if M2's adapter meets its target: sleep trains the adapter from the day's pairs and the proxy serves it agent after M2
Launch A1–A4 met, A5 at 20 per arm the paper's §7 with frontier numbers; the name decided (done: Neverest, 2026-11-15); the repository and the commons opened owner: the name and the go not yet

Open questions the program answers along the way: why memory up front raises hand-backs (A3); whether a lesson's content adds to the moment (0.7.0: reminder 6% against a bare nudge 9%, p = 0.09); whether a working reminder makes its own lesson fade (a confirmed correction means the agent failed; see below).

Where we left off (2026-11-15)

The latest state, for whoever picks this up next (a person or an agent):

Next proof of value

The next milestone is one coding workflow that demonstrably repeats fewer mistakes, rather than more transports or a larger model. Keep the existing goal targets in GOALS.md fixed; do not relabel the present evidence as success.

  1. Reliability before wider use. Merge only after the regression and docs checks pass. Check a clean install, a two-memory revoke/render cycle and the proxy with both API formats before preparing a release. Preserve the existing full release check as the gate for deployment and installation.
  2. Make setup understandable. Add a read-only neverest doctor that reports the executable version, store, registered integrations, hook commands and last successful sleep, with concrete fixes. Acceptance: a new user can diagnose a missing integration without editing configuration by guesswork; the command changes no files.
  3. Measure one real outcome. For one project, collect the existing shown/held-out samples until each arm meets A5's predeclared minimum, then report repeats, false alarms, reminder frequency and latency alongside the baseline. A confirmed prediction is a repeated mistake, not proof that the intervention prevented it.
  4. Prove transfer before opening the commons. Run the two-machine A9 trial with a deliberately non-private error lesson; show local evidence, imported candidate, verification and revocation. Keep the privacy and trust boundaries visible. Broader federation and nightly adapters follow evidence, not precede it.

Earlier work

Phase 0: the organism (done, 0.1.0)

Ingest, recall, sleep, render, MCP, for one Claude Code user on one machine. No model required.

Phase 1: make it true

Phase 2: two agents

Phase 3: compiled memory

Phase 4: the raw stream beyond the terminal

Phase 5: the commons

Phase 6: the breathing cycle

Launch

The repository goes public when phase 1's measurements exist and the paper's §7 has its first numbers. The name is Neverest since 2026-11-15 (Everest for a few hours that day, Everist in 0.10.0; it was Open Memory until 0.9.0, which collided with mem0's OpenMemory MCP server, and Remem in 0.9.x, a name several other memories for coding agents use).