Jul 6, 2026
What is an AI work platform? (and why it beats four tools)
Everyone renamed their tracker an AI work platform in 2026. Here is what the term should mean — and the test for a real one versus AI bolted onto an old app.
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Dmitrii Selikhov
Founder
Dmitrii Selikhov is the founder of Planoda and a lead full-stack engineer with 15+ years building developer tools and leading teams as a technical lead, software architect, and CTO.
46 posts by Dmitrii Selikhov.
Jul 6, 2026
Flow metrics: the four numbers that predict delivery
Velocity tells you how busy a team was. Flow metrics tell you when work ships — WIP, cycle time, throughput, and age, the four numbers that forecast it.
ReadJul 6, 2026
Audit trails for AI agents: what auditors ask for
When an agent changes a record, can you say who, what, and who approved it — months later? An audit trail for agents, and what a compliance review will ask.
ReadJul 6, 2026
An AI governance framework you can actually run
NIST AI RMF and ISO 42001 say what good AI governance looks like. Here is how to run it for agents that act — mapped to controls a platform can enforce.
ReadJul 6, 2026
No-code AI agents: build a teammate, not a macro
Describe what you want and get an agent — every 2026 tool sells this. The question that matters: can a no-code agent act safely, under review, on real data?
ReadJul 6, 2026
From meeting notes to tracked work, automatically
An AI notetaker whose summary nobody acts on is theater. The real test: whether decisions and action items become tracked, owned, governed work — not a doc.
ReadJul 6, 2026
Capacity planning without the spreadsheet gymnastics
Most capacity planning is a spreadsheet that is wrong by Wednesday. Plan real capacity from live signals — availability, WIP, and throughput — not a guess.
ReadJul 6, 2026
Sprint planning with AI: faster, and still yours
AI can draft the sprint in seconds, but the plan is still yours. How to use an agent to prep, scope, and forecast a sprint without losing the judgment calls.
ReadJul 6, 2026
How to switch project management tools: a 2026 checklist
Switching tools is where good intentions go to die. A tool-agnostic checklist for moving your team — data, workflow, and habits — without a lost quarter.
ReadJul 6, 2026
How to migrate from ClickUp without inheriting the bloat
ClickUp does everything — including slow you down. A practical path to move issues, docs, and automations onto one schema without losing history or momentum.
ReadJun 21, 2026
Notion's agent orchestration vs governed agents: per-agent vs per-action
Notion turned its workspace into a hub that orchestrates outside agents, governed by admin gatekeeping and per-agent credit limits. Planoda governs the other way — per-action propose-and-approve. Here's why the unit of control matters more than the orchestration layer.
ReadJun 21, 2026
Linear Agent vs Planoda: autonomous coding vs governed agents
Linear shipped the strongest in-tool coding agent of 2026 — triage to reviewed fix without leaving the tracker. Planoda bets on a different axis: cross-functional agents under a propose-and-approve broker. An honest comparison of where each one genuinely wins.
ReadJun 21, 2026
Propose & approve: let AI agents act without losing control
An AI agent that can change your data needs more than a kill switch. Here's the propose-and-approve broker model — per-action review, immutable audit, and a cost ledger — that lets agents do real work while a human stays accountable for every consequential change.
ReadJun 21, 2026
Why metered AI credits cost more than they look
Across 2026 the work-platform industry quietly moved AI onto metered credits on top of the seat — ClickUp, Notion, Monday, Atlassian Rovo, Asana, and more. Here's why per-credit pricing makes adoption fight your own budget, and what a transparent per-seat model changes.
ReadJun 21, 2026
AI work platforms in 2026: every major agent feature, compared
In 2026 Linear, ClickUp, Monday, and Notion all shipped agents that take action — coding sessions, assignable AI coworkers, no-code app builders, external-agent orchestration. Here's what each actually shipped, where they converge, and the one axis nobody else made native.
ReadJun 20, 2026
Agent governance and the EU AI Act: what changes for work platforms
As AI agents move from suggesting to acting inside your work platform, 'who approved this?' stops being a nice-to-have and becomes a compliance question. A practical look at why propose-and-approve, immutable audit trails, and per-workspace cost control are becoming table stakes.
ReadJun 20, 2026
How to run OKRs that don't rot by week three
Most OKRs die quietly: written in a kickoff doc, copied into a slide, never updated again. The fix isn't a better template — it's putting the objective on the same schema as the work, so progress rolls up by itself and a stale number is impossible.
ReadJun 19, 2026
How to choose an AI project management tool in 2026
Every tool says it has AI now. The buyer's question isn't whether — it's how. A practical evaluation guide: AI-native vs bolted-on, governance and audit, the per-seat vs metered-credit cost trap, data privacy and no-train terms, and why a unified schema beats a chat panel.
ReadJun 18, 2026
Will AI replace project managers?
No — but the job is changing fast. AI is on track to automate most routine PMO work by 2030; what it can't do is own the consequential decisions. An honest look at which parts of the PM role vanish, which get harder, and what stays human.
ReadJun 17, 2026
Templates are a growth loop, not a content dump
Most product teams treat their template gallery as a dumping ground that quietly rots. Treated as an onboarding engine and a time-to-value lever, the same gallery becomes one of the strongest growth loops you have.
ReadJun 16, 2026
Why AI governance is the real moat in work tools
Every work tool now has AI. The model isn't the moat — anyone can call the same API. The durable advantage is governance: who can prove their agents are safe to turn on.
ReadJun 16, 2026
Forecast delivery dates without estimating a thing
Story-point estimates are slow, contentious, and usually wrong. Probabilistic forecasting answers 'when will it ship?' with a confidence level — using only the completion data your team already produces.
ReadJun 13, 2026
Customer health, beyond the vanity dashboard
Most customer health scores measure what already happened and feel reassuring right up until the churn email arrives. A health score worth having predicts, and predictions look backward only at your peril.
ReadJun 12, 2026
Propose-and-approve: designing agent autonomy you can trust
Full autonomy is reckless and full manual review defeats the point. Propose-and-approve is the middle path — and getting the boundary right is the whole design problem.
ReadJun 11, 2026
DORA metrics without the dashboard theater
The four DORA metrics are the best-validated measure of delivery performance there is — and the easiest to turn into vanity dashboards. How to use them to find bottlenecks instead of to grade people.
ReadJun 9, 2026
The hidden cost of ungoverned AI agents
An ungoverned agent looks free in the demo. The real bill arrives later — in surprise spend, stalled security reviews, and the day you can't explain what it did.
ReadJun 9, 2026
Keyboard-first product management: speed as a feature
The fastest UI is the one your hands never leave. Why keyboard-first product management isn't a power-user nicety — it's the difference between a tool you use and a tool you fight.
ReadJun 9, 2026
Error budgets: stop arguing, start subtracting
The eternal fight between shipping features and keeping things stable is unwinnable as an argument. An error budget converts it into a number both sides have already agreed to.
ReadJun 7, 2026
Human-in-the-loop AI agents: autonomy you can trust
Fully autonomous agents are a demo; supervised agents are a tool. Why the propose-approve boundary — not raw capability — is what makes AI agents safe to leave running on your real backlog.
ReadJun 5, 2026
Cycle reviews: closing the loop on every sprint
Planning a cycle is the easy half. The review at the end — what shipped, what slipped, and why — is where teams actually get better. How to run a cycle review that changes the next plan instead of just narrating the last one.
ReadJun 5, 2026
Prompt injection is the new SQL injection
Every team rushing AI into their product has reopened a class of vulnerability we thought we'd solved. Most AI tools are wide open. The defense is old, boring, and entirely ignored.
ReadJun 4, 2026
MCP, explained for work platforms
The Model Context Protocol lets any AI client reach your work tool's data and actions through one standard interface. Here's what it is, why it matters, and how to expose it without handing an agent the keys.
ReadJun 4, 2026
Cycle planning that survives reality
Most sprint plans are fiction by Wednesday. How to plan cycles that bend instead of break — scoping for the interruptions you know are coming, not the ones you wish weren't.
ReadJun 2, 2026
Migrating from Jira without losing your history
The thing that keeps teams on Jira isn't the tool — it's the years of issue history, links, and keys they're afraid to lose. Here's how to move all of it across intact.
ReadJun 2, 2026
OKRs vs KPIs: the goal is not the gauge
Teams confuse the goal they're chasing with the gauge that measures it, then wonder why their dashboard is full and their direction is empty. The difference, and why it matters.
ReadMay 28, 2026
Why one tool beats three for shipping work
Issue tracker, kanban board, and a roadmap doc nobody updates — the hidden tax of a fragmented stack, and what consolidating actually changes.
ReadMay 26, 2026
How AI triage actually routes work
A look under the hood at what happens between a raw inbound message and a structured, assigned issue — the steps, the signals, and where the human stays in control.
ReadMay 21, 2026
How to control AI spend with a per-workspace cost ledger
AI features die from unpredictable bills as often as from bad output. A per-workspace cost ledger — preflight before the call, record after — is how you leave the agent running without fearing the invoice.
ReadMay 21, 2026
Why boards and issues belong on one schema
A board and an issue tracker aren't two products — they're two views of the same data. What goes wrong when they're separate systems, and what gets simpler when they aren't.
ReadMay 19, 2026
The real cost of tool sprawl (with the math)
Every tool is individually affordable, which is exactly how the bill gets out of hand. A worked example of what a fragmented stack actually costs — in dollars and in hours.
ReadMay 14, 2026
AI triage that actually pays its way
Most AI features are demos. Here's how auto-prioritization and routing remove real busywork from inbound requests — and how to keep the cost honest.
ReadMay 7, 2026
Migrating from Linear, Jira, or ClickUp without a quarter-long project
The fear that switching tools eats a quarter is what keeps teams stuck. It doesn't have to — a phased, one-team-at-a-time migration ships value in days and never bets the org on a single Monday.
ReadMay 7, 2026
Shipping changelogs your customers actually read
Most changelogs are a graveyard of version numbers nobody opens. How to write release notes that customers look forward to — and that double as your best retention channel.
ReadApr 30, 2026
Designing for sub-100 ms (and why it matters)
Latency is a feature. A look at the architecture choices — realtime fabric, optimistic updates, an offline-capable PWA — that keep every interaction under 100 ms.
ReadApr 23, 2026
Designing a team of agents, not one monolithic AI
A single all-powerful AI is harder to trust, harder to bound, and harder to debug than a team of small, scoped agents. The design pattern that makes multi-agent systems both safer and more capable.
ReadApr 9, 2026
Security without the questionnaire dread
Row-level security, SSO/SAML, SCIM, and an immutable audit log — the controls that turn a multi-week security review into a one-day sign-off.
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