Product management for the AI era

Building got fast. Deciding didn't.

When AI accelerates delivery, the bottleneck moves upstream to product decisions. Telos is built for that work.

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The Telos operating model

Vision → Tasks

Vision

1 active

Objectives

Opportunities

Tasks

312

Other tools track what you're doing. Telos remembers what you've decided and why, and makes every next decision sharper.

The shift

How product teams will operate when AI does the building.

When delivery stops being the constraint, the upstream work needs its own infrastructure. This is what that looks like.

Vision is the root object. Every decision descends from it.

Problem: When 8 people become 40, the founder stops being the alignment system. Decisions multiply faster than anyone can track. Every standup re-litigates what matters because the prior call lives in someone's head or a Notion doc nobody re-reads.
Solution: In Telos, Vision is a real entity. Objectives descend from it, each anchored to a Metric the org has signed up to move. Strategies and customer insights inform those decisions from the side, not from above. Every Opportunity and Task traces back to a vision in a query, not a slide. Reorganize at the top, the org sees the consequences immediately.

Informs decisions

Stakeholder visibility is the highest-leverage unlock for growthStrategy

Signups this quarter: 12Metric

Become the go-to tool for outcome-driven product teamsVision

Launch publicly and reach 50 signups this quarterObjective

No easy way to share the roadmap with stakeholdersOpportunity

Add one-click shareable roadmap viewTask

Teams get problems to solve, not features to build.

Problem: Most product orgs hand engineers feature tickets. The roadmap is a list of things to build, not outcomes to deliver, and the team's job becomes throughput on someone else's brief. When AI takes the building work, that model collapses. The unique human contribution moves upstream, to figuring out what would actually work. Feature-list roadmaps don't generate that judgment. They suppress it.
Solution: Leadership commits to Objectives, each anchored to the Metric the org has signed up to move. Teams own the discovery: which Opportunities to attack the Objective with, which to reject, which evidence supports each bet. The roadmap isn't a list of features. It's the outcomes the company chose, and the bets the teams are running to move them.

Set by leadershipOBJECTIVE

Lift activation to 45% by year-end

Metric · Activation rate · currently 34%

Opportunities · chosen by product & engineering

Simplify onboarding flowest. +6 pp

Magic-link signupest. +3 pp

Personalize first-run experienceest. +2 pp

Product discovery as a first-class workflow.

Problem: When building is fast and cheap, discovery and deciding become the rate-limiting step. With AI, teams can now fully build and ship a solution before realizing it doesn't solve the client's actual problem faster than ever before.
Solution: Telos structures discovery as a workflow your team configures. The four product risks are fixed checkpoints every Opportunity goes through. You can move to delivery with risks flagged. The tool never blocks you. What changes is that the call is now explicit: visible, owned, not stored in someone's head. Invisible friction that nudges the hard questions before the build, and keeps the feedback loop with clients fast.

Audit log for complianceDiscovering

Value

8 enterprise deals require it

Usability

3 prototypes tested

Feasibility

Log retention storage not provisioned

Viability

Enterprise tier only · +14pp margin

Commit gate3/4 validated · READY

Every insight tied to a Client. Evidence as a primary asset.

Problem: Build verbatim for the loudest client and you miss the pattern. Eight others asked for something related, three with deadlines you already committed to. The signal is there. It's buried across calls, docs, and notes nobody re-reads.
Solution: Clients are first-class entities. Each Insight is captured with an interpretation, a MoSCoW priority, and the client's stated deadline. Read across Insights to surface patterns your backlog cannot show. The agent flags when a request matches something the team already evaluated and rejected, and why. Every client commitment is tracked, visible at planning time, and factored in when priorities shift. The result is clarity on blast radius and no forgotten committed deadlines.

Maple Analytics

Active · since 2024-Q1

$480K ARR

Every time I need to show the board our progress against targets, I have to ask the data team for a custom export. By the time it lands, the numbers are already stale.

SARAH K · HEAD OF PRODUCT · MUST-HAVE · DEADLINE: AUG 31, 2026

LINKED OPPORTUNITIES

Unified reporting dashboardin discovery

Scheduled report exportsproposed

Workflows with constrained flexibility. Opinionated on ownership, flexible on shape.

Problem: Most PM tools quietly run on a power user. Every team works differently, so the tool is built flexible, and one person wrestles that flexibility into a convention and pushes it top down. They remember it. The team doesn't, because the tool lets you do whatever you want, and new hires spend a month decoding 'how we actually operate' from Slack threads. Going rigid is no answer either: a tool that forces convergence gets abandoned for a Notion doc, and free-form boards turn into voids where specs sit in 'In Progress' for weeks because nobody owns the next step.
Solution: Telos is opinionated where it matters and flexible where it doesn't. You define the shape (intake, triage, solutions design, delivery, measure, whatever your team actually does). Telos enforces the one thing that breaks without structure: every step has a named owner. The workflow is the operating manual. Once it's set, everybody works the same way, and that's the feature. Open Telos on day one and a new hire knows who owns what, when.

Discovery to DeliveryWorkflow · 9 steps

01Customer insight collationMLMaria LDone

02Value assessmentAKAnya KDone

03Team syncMLMaria LDone

04PrototypingJRJordan RIn progress

05Customer feedbackSTSam TQueued

06Final PRDMKMira KQueued

07BuildSTSam TQueued

08MeasureAKAnya KQueued

09LearnMLMaria LQueued

Unified reporting dashboard is at Prototyping. Jordan was notified with a hand off message from Maria.

An agent that has read everything your org has decided.

Problem: Every product decision arrives with local context: the customer who asked, the urgency of the moment, the engineer ready to build. What it doesn't arrive with is what your org already knows. The strategy it conflicts with. The Opportunity you rejected six months ago for exactly this reason. The Objective it won't move.
Solution: When an Opportunity is created, an agent reads your full strategic stack: Vision, Strategies, Objectives, and the Insights your team has captured. It flags conflicts, surfaces prior decisions, and proposes Opportunities your existing evidence already supports. It shows up at the decision moment with the context loaded. AI challenge and recommends. You make the call.

Agent reviewUnified reporting dashboard

Vision alignment8 / 10

Strategy alignment1 conflict

Objective progressionYes

Prior decisions1 conflict

Review

Vision. Strong fit. The opportunity directly supports reducing time-to-insight for teams, which is central to the active vision.

Strategy. One flag. TS-2 requires Postgres for all non-time-series data. The proposed reporting layer references a separate analytics store. Resolve the architecture before build.

Objective. Likely to move activation rate. Customer feedback from 3 enterprise accounts, including Maple Analytics, shows reporting gaps are a direct blocker to daily active use.

Prior decision. A similar scope was explored as OPP-091 in Q3. Confirm the delta is additive and not overlapping before committing scope.

Where the money actually went. For the executive at the top.

Problem: Executives need a clean answer: 'what did we actually fund this quarter — features, bug fixes, maintenance, or architecture?' Today that answer comes from someone exporting four tools, burning a bunch of tokens or joining the data in a spreadsheet.
Solution: Telos categorizes every Opportunity and Task by workflow type and rolls engineer-hours into a live time-allocation breakdown. Open the dashboard, see the split. Drill into any slice. Compare quarters. The executive overview lives in the same tool the engineers use, and it's never more than one click stale.

Q3 time allocation$2.12M · 40 eng

Features42%$890K

Maintenance24%$510K

Bug fixes18%$380K

Architecture16%$340K

Maintenance is up +6 pp vs. Q2. Open the slice to see which Opportunities drove it.

An engine for saying no, so every yes ships in alignment.

The decisions compound.

Telos makes every product decision a building block. Captured Insights, reasoned Opportunities, recorded kills. After a year, your institutional knowledge is structured and queryable. Not buried in Slack.

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