Step 1
Know what was decided, by whom, and why
Use decision records as durable institutional memory during delivery, incidents, and audits.
Decisions shape everything. It's time we treated them that way.
dlogs helps teams capture key decisions where work happens and retrieve them across web, Slack, GitHub, Linear, APIs, and MCP workflows. Build durable decisions intelligence over time.
Free beta, all features unlockedAppend-only and tamper-evidentHuman-first, agent-ready
How this works and how this helps
In every organization, decisions happen across functions and surfaces. dlogs stores key decisions in structured form so they stay queryable for humans and agents.
Decisions are born everywhere
Important decisions happen in meetings, chat threads, issue trackers, and code changes.
Most decisions are not retrievable
When context is lost, teams repeat tradeoffs, miss constraints, and cannot trace outcomes back to the original call.
dlogs stores key decisions, not everything
We capture the consequential records that matter and make them queryable by humans, APIs, and MCP clients.
What this unlocks
Step 2
Connect outcomes back to decisions
Understand which choices led to which results, and what constraints still apply.
Step 3
Compare new decisions with prior ones
Before making a new call, check similar historical decisions and supersede chains.
Where decisions are born, where they are found
Capture
Slack
Capture and retrieve decisions in live conversations.
GitHub
Capture decisions alongside code changes, with optional enforcement.
Linear
Store and retrieve product and delivery decisions from planning workflows.
Cursor and VSCode
Capture and retrieve decision context from editor workflows via MCP.
Retrieve
Web app
Browse decisions, lineage, and context in one place.
APIs
Integrate decision context into internal tools and automations.
MCP
Let humans and agents query decisions from IDE and workflow clients.
Slack and Linear
Get decision context where teams collaborate and plan work.
@dlogs in Slack. Query decisions. Record new ones. Without leaving the conversation.
Your team makes decisions in Slack every day. dlogs meets you there — retrieve context during incidents and capture decisions before the thread gets buried.
RetrieveGet decision context in seconds
# incident-auth-2026-03Active
AK
alex.kim2:09 AM
Something changed in token rotation recently.
@dlogs auth token rotation
dl
dlogs2:09 AM
DEC-2026-0042 · ACTIVE
Set token rotation to 24h window
Constraint: must not exceed Redis connection pool limit
Supersedes: DEC-2025-0018
View full decision →
AK
alex.kim2:14 AM
Found it. Pool config was never updated after DEC-2026-0119. Fixing now.
RecordCapture decisions before the thread gets buried
# eng-platform
PR
priya3:42 PM
OK so we're going with Redis cluster over Memcached. Write-through handles our consistency needs. We accept higher memory cost.
AK
alex.kim3:45 PM
Agreed. Let's record this before it gets buried.
/dlogs record
dl
dlogs3:45 PM
Decision form opened · AI pre-filled from thread context
TitleAdopt Redis cluster with write-through caching
ProblemNeed consistent cache layer for session state
OptionsRedis cluster, Memcached, DynamoDB DAX
Review and edit in the modal, then submit.
dl
dlogs3:46 PM
Recorded · DEC-2026-0089
Adopt Redis cluster with write-through caching
By @alex.kim · Linked to this thread
View full decision →
GitHub: capture decisions alongside code changes
Enforcement can be enabled where teams want stronger governance, but capture and retrieval work even without merge blocking.
Step 1
The PR
A developer opens a PR that modifies a protected file.
- Title: Upgrade RDS instance to r6g.xlarge
- File touched: infra/terraform/rds.tf
- Policy match: infra/**
Step 2
The block
dlogs can flag missing decision context when policy is enabled.
- Optional policy: dlogs/decision-context requested.
- This PR modifies a high-impact path.
- Bot comment suggests linking an existing decision or creating one.
Step 3
The decision
The developer writes a quick decision record.
- Decision ID: DEC-2026-0042
- Problem: CPU ceiling during peak traffic windows.
- Decision: Upgrade now; revisit read replicas next quarter.
Step 4
The merge
Decision is linked and PR now carries durable context.
- dlogs/decision-context: Decision DEC-2026-0042 linked.
- Status: Active and retrievable
- Merge proceeds with durable decision context.
Ask @dlogs in your editor. Understand any function's decision history.
Ask a question about any function. dlogs matches it to the exact decision that governs that code, including constraints, tradeoffs, and the full supersede chain.
auth/token_rotation.pyCursor
40
41# Token rotation strategy
42def rotate_token(user, window_hours=24):
43 """Rotate auth token within the given window."""
44 pool = get_redis_pool()
45 if pool.active_connections > pool.max - 2:
46 raise PoolExhaustedError()
47 token = generate_token(user)
48 cache_token(pool, token, ttl=window_hours * 3600)
49 return token
50
dlogs
@dlogs why does rotate_token use a 24h window?
DEC-2026-0042ACTIVEsymbol: rotate_token
24h window balances token freshness against Redis connection pool limits. 1h window (DEC-2025-0018) was rejected for causing latency spikes under load.
Constraint: Redis pool max connections
Supersedes: DEC-2025-0018
View full decision →
Linear: store and retrieve decision context in planning workflows
Product and delivery decisions are just as consequential as code decisions. dlogs links planning context to implementation context.
Store
Capture decision context from issue planning
Save key rationale, constraints, and ownership from issue discussions so future execution is grounded in explicit decisions.
Retrieve
Query decision history from delivery context
Before opening a new initiative, compare against prior related decisions and lineage so teams avoid repeated mistakes.
Trust guarantees, not conventions
Append-only by design
Decisions are never edited or deleted. New facts supersede old ones; history stays intact.
Trust over convenience
Tamper-evident, hash-chained records and derived status prevent silent drift from truth.
AI suggests, humans author
AI may suggest topics and gaps. It does not own decisions; your team remains accountable author.
The merge is not the end. It is where future clarity starts.
Six months after a decision was captured, it pays for itself when the next team needs to understand why.
Decision lineage for infra/terraform/
DEC-2025-0018superseded
Initial RDS sizing for launch
@vamshi · Sep 2025
Constraint: Stay under $500/mo during beta
superseded by ↓
DEC-2026-0042superseded
Upgrade RDS to r6g.xlarge
@priya · Jan 2026
Constraint: Must not exceed Redis connection pool limit
superseded by ↓
DEC-2026-0119active
Add read replicas for auth DB
@alex · Mar 2026
Constraint: Pool config must be updated to match replica count
Postmortem finding
DEC-2026-0119 added replicas without adjusting pool limits. The binding constraint from DEC-2026-0042 was still in effect. Root cause identified in minutes using the decision chain.
Use the product first. Build intelligence from real decision data.
We are focused on seamless adoption first: sign up, capture key decisions, and retrieve them reliably. As immutable decision records accumulate, we build deeper intelligence on top using conventional software and modern LLM systems.
- Today: store key decisions from code, chat, planning, and app workflows.
- Near term: strengthen retrieval across humans and agents via API and MCP.
- Next: decision intelligence graph, relationship mapping, and consequence-aware insights.
FAQ
Is dlogs free right now?
Yes. dlogs is in free beta for everyone who wants to use and experiment with it.
Is there a pricing plan right now?
No. We are not charging during beta. We want teams to use dlogs, shape workflows, and help us learn before packaging decisions.
What is dlogs in one line?
dlogs is a decisions intelligence platform that stores key decisions as immutable records and makes them queryable across tools.
Who is dlogs built for?
Humans first: people making system, product, and strategy decisions. Agents second: agentic workflows that need reliable decision retrieval and capture via MCP and APIs.
Does dlogs store everything?
No. dlogs is selective by design. It stores key consequential decisions, not every message or artifact.
Does AI write decisions for us?
No. AI can help suggest or summarize context, but humans author and own decision accountability.
Where can we capture and retrieve decisions?
Capture and retrieval are supported across web, Slack, GitHub, APIs, MCP clients, and editor workflows. Linear support is part of the planned expansion path.
Is GitHub enforcement required?
No. Enforcement is optional. Teams can use dlogs for pure capture/retrieval or enable policy checks where they need stronger governance.
Why does immutable history matter?
It protects decision integrity over time. Teams can see what changed, what was superseded, and why a choice existed at a specific moment.
What is the long-term direction?
Let teams use dlogs first, grow high-quality immutable records, then build richer intelligence on top: related decisions, consequence mapping, and decision graph insights.
Start recording key decisions now. Build intelligence over time.
dlogs is free during beta. Capture from where work happens and keep future decisions grounded in durable context.