Product and roadmap management

Set up and run product operations workflows in Airtable — roadmap, customer feedback, launches, OKRs, sprints, releases — adapting to the user's team size, sub-workflow priorities, and customer shape. Ask scope before scaffolding; the same trigger can mean a 3-table solo workspace or a multi-base enterprise portfolio, and the right schema depends on what the user is actually trying to coordinate.

Who this serves and what they're solving for

Three product-shape buckets, each with distinct personas and pain:

• Software product team — the obvious-looking default that's actually less than half of real-world cases. PMs, PMMs, engineering leads, designers, founders / PM-of-one. Top priorities: roadmap visibility for execs and GTM, feedback-to-feature linkage with demand signal, OKR cascade, launch coordination, capacity-vs-commitments clarity. Modal pain: tool sprawl across Productboard / Jira / Smartsheet / spreadsheets / slide decks — "swivel-chair work," "too many sources of truth," "PMs spending 2-3 hours/week searching and copying data," "40% of PM time answering internal roadmap questions," feedback "living in a 'black hole.'"
• Non-tech industry product teams. Product managers in apparel / fashion / consumer (PLM-shaped — line plans, BOM, tech packs, sample tracking), banking / fintech / capital markets (regulated and stage-gated), pharma / biotech / medical devices (compliance-heavy), media / gaming (release-cadence and franchise portfolio), aerospace / automotive (APQP and supplier-collaborative). Top priorities: product lifecycle management with phased compliance, vendor / partner coordination via synced bases, BOM and SKU governance, ROI / IRR / NPV business-case reviews on initiatives, regulated audit-trail rollups. Modal pain: aged PLM / SoR systems that "haven't been touched," Excel sprawl with version clashes, the "translation layer" need between specialist tools and executive review, regulatory audit-trail requirements that current tools don't enforce.
• Multi-team product ops at scale. Product Ops Leads, Directors of Product Operations, PMO directors at large product orgs, VPs of Product. Top priorities: portfolio rollup across squads, capacity-constrained planning with cut-line scenarios, cross-team dependency tracking, OKR alignment for hundreds of initiatives, mobile-friendly executive dashboards. Modal pain: "weekend reporting marathons," portfolio drift between strategic intent and operational work, "limited Jira literacy outside Product/Engineering," "manual translation of Jira data for executives."

Broader problems running across all three:

• Tool sprawl and broken single source of truth. A single base often replaces 5+ tools — PM tool + engineering tracker + spreadsheets + slide decks + email threads. The first job is often to consolidate, not just add another tool.
• Manual reporting toil. Status updates, executive decks, weekly digests, QBR prep — a meaningful chunk of PM time goes into producing reports a system could generate. Automating this is usually the highest-leverage early win.
• Feedback-to-feature disconnect. Customer signal arrives across channels (NPS, support tickets, Slack, sales notes, in-app, call transcripts) but doesn't trace to roadmap decisions — feedback "lives in a 'black hole'" without a structured link from raw signal to demand-weighted prioritization.
• Cross-functional handoffs dropping. Design → Engineering → Marketing → CS handoffs lose fidelity without explicit ownership, dependencies, and shared schema.
• Aspirational vs. deployed AI. Most customers are still piloting AI in product ops, not running it in production. Workflows should compose AI cleanly when available but work without it.