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Elpis
Terminal environment that keeps your AI agent's context lean
Elpis is a terminal environment for coding agents, built on OpenAI's Codex CLI. The core problem: long agent sessions bury useful state under the history of how the agent got there. Every request pays for all of it. Elpis separates working context from durable evidence. After each turn, a meaning-aware pruner (Ace) evicts completed tool outputs, resolved dead ends, and low-signal history from the live context to disk. The next request starts lean.
Elpis is a terminal environment for coding agents, built on OpenAI's Codex CLI.
The core problem: long agent sessions bury useful state under the history of how the agent got there. Every request pays for all of it.
Elpis separates working context from durable evidence. After each turn, a meaning-aware pruner (Ace) evicts completed tool outputs, resolved dead ends, and low-signal history from the live context to disk. The next request starts lean.
Measured against the Codex CLI baseline on the same task: Elpis finishes with 93% context free; Codex finishes at 73%.
Features:
• Context Ledger — always-visible working set with ctrl+clickable paths
• Portable continuity — goal and checkpoint state survive restarts
• Bounded memory — selective, size-capped, attributable
• Explicit provider choice — OpenAI, Anthropic, Gemini, OpenRouter
• No analytics by default
v0.1.1 · Linux x86_64 · Open source (MIT)
The meaning-aware pruner is a clever move. Skipping the rerun-token tax on resolved dead ends is the kind of detail that separates a polished tool from a clever demo.
About Elpis on Product Hunt
“Terminal environment that keeps your AI agent's context lean”
Elpis was submitted on Product Hunt and earned 3 upvotes and 2 comments, placing #154 on the daily leaderboard. Elpis is a terminal environment for coding agents, built on OpenAI's Codex CLI. The core problem: long agent sessions bury useful state under the history of how the agent got there. Every request pays for all of it. Elpis separates working context from durable evidence. After each turn, a meaning-aware pruner (Ace) evicts completed tool outputs, resolved dead ends, and low-signal history from the live context to disk. The next request starts lean.
Elpis was featured in Software Engineering (42.8k followers), Developer Tools (516.4k followers), GitHub (41.3k followers) and Vibe coding (588 followers) on Product Hunt. Together, these topics include over 111.2k products, making this a competitive space to launch in.
Who hunted Elpis?
Elpis was hunted by Masih Maafi. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Elpis stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Masih Maafi