Shivam.Consulting Blog
AI products, enablement & hiring
- AI Strategy (274)
- Generative AI (105)
- IT Leadership (32)
- Leadership (78)
- Product Management (324)
- Product Management Leadership (286)
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Developer-First Growth: From Fast Activation to Revenue
A practical playbook for turning fast developer activation into team expansion, coherent packaging, and durable enterprise revenue.
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An Operating System for AI-Era Product and Engineering Leaders
A practical model for turning faster AI-assisted output into reliable customer outcomes through clear bets, evals, decision rights, and learning loops.
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Enterprise GTM: Build One System From Pipeline to Expansion
A practical operating model for connecting qualification, champions, pilots, onboarding, value realization, renewal, and enterprise expansion.
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From Product-Market Fit to Expansion: A Sequencing Model
A practical model for proving product-market fit, choosing the right expansion path, protecting the core, and scaling adjacencies with evidence.
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What Makes or Breaks Executive Hires: My Lessons on Fit, Red Flags, and Measuring Success
Executive hiring is a make-or-break decision that demands clarity on fit, scope, and measurable outcomes. In this deep dive with Eeke de Milliano, I unpack the…
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How to Create a B2B Category and Scale the GTM Motion
A practical operating model for choosing category creation, proving a practitioner wedge, designing monetization, and scaling from PLG to enterprise.
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Persuasive Leadership for Founders: My Take on Wes Kao’s Playbook to Influence and Win
Founders and product leaders don’t need more noise—they need persuasive clarity. In this first-person breakdown, I share how to align your message with your natural style,…
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When a Focused Product Wedge Is Ready to Become a Platform
A practical framework for deepening a winning wedge, extracting reusable platform primitives, and expanding without weakening product-market fit.
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How to Build an AI-Native Product Team Operating Model
A practical operating model for AI-native squads, platform services, decision rights, evaluation gates, metrics, and a disciplined 90-day rollout.
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Reliable AI Product Systems: A Product Leader’s Playbook
A practical operating model for defining reliability, designing bounded AI workflows, building evals, and controlling releases in production at scale.
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Deliberate Practice for Product Teams: How AI and On‑Demand Learning Unlock Mastery
Deliberate practice is the missing link between product learning and lasting behavior change. In this episode recap, I share why a blended model—cohort-based structure plus on-demand…
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Inside Alyx: Dogfooding, Evals, and Observability That Power an Agentic AI Future
This is a pragmatic, first-hand look at how Alyx was built by dogfooding Arize’s own platform—moving from messy notebooks to a disciplined eval and observability stack.…
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How to Design Your Product Leadership Legacy: Impact, Craft, and Values That Endure
This reflection-driven episode challenged me to define the product leadership legacy I’m actively building—today, not someday. I share how I reframe “legacy” into actionable questions for…
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AI Coworkers That Actually Work: Inside Neople’s Guardrails, Evals, and Customer-Ready Agents
I explore how Neople builds “digital coworkers” that blend automation reliability with AI flexibility to handle real customer work. You’ll see how the team balances code,…
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How Braintrust Nailed Product-Market Fit: Paranoia, Patience, and High-Bar Quality
Braintrust’s playbook for product-market fit in GenAI pairs a relentless quality bar with deliberate go-to-market restraint. By transforming evaluation pain into an end-to-end platform for building…
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Inside the AI‑First Web: Designing Agent‑Friendly APIs, Prioritizing Accuracy, and Scaling Trust
AI is becoming the web’s second user, and that reality changes how we design, measure, and monetize our products. I break down why accuracy must beat…
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From Product-Market Fit to Scale: A Phase-Gate Playbook
A practical phase-gate framework for proving customer pull, choosing the right growth motion, scaling execution, and expanding without diluting fit.
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Stop Monitoring Systems—Start Monitoring Outcomes with Heartbeat Metrics That Protect Trust
Outcomes beat dashboards. By centering on heartbeat metrics—signals directly tied to customer value—you detect incidents faster, align engineering on what truly matters, and make SLAs meaningful.…
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Leading Support with AI Metrics: How CX Score Transformed Our Scale and Mindset
AI metrics have changed how I lead support, from the questions I ask to the processes I run. With CX Score, we went from limited CSAT…
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Cut Through AI Hype: A Product Leader’s Guide to Vet, Buy, and Deploy with Confidence
AI can deliver real outcomes, but only if you choose and implement it deliberately. I share the core concepts leaders need — RAG, vector search, agentic…
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- AI Strategy (274)
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