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Where business meets innovation and technology drives transformation. Concept to Cloud is the podcast for leaders navigating the forgotten ground between startup chaos and enterprise bureaucracy. If you're building and scaling teams at organizations in the middle — where startup rules no longer apply and enterprise playbooks are far too large — this show is for you. Hosted by Tom Barber, each episode explores the real challenges facing today's engineering leaders: scaling systems without breaking them, building high-performing teams, aligning engineering strategy with business goals, and making technical decisions that drive measurable impact. Whether you're a Director of Engineering, VP of Technology, CTO, or an IC engineer stepping into leadership, you'll find practical insights drawn from real-world experience — not theoretical frameworks that only work on whiteboards. Topics include: Scaling engineering teams and systems for growth Building effective engineering culture Bridging
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Signup to Generate a PitchConcept To Cloud is a technology podcast hosted by Tom Barber, with 18 episodes on record and a Required Pod Score of 80.
Tom Barber hosts Concept To Cloud, a technology show with 18 episodes published.
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Concept To Cloud
Tom rebuilt Saiku - an open-source analytics platform he first shipped years ago - and got 97 new installs. He also found roughly 180 people still running the old one. He can't email them. He can't see them. Two-thirds of them are on a version that nee...
Episode #17
In this episode of Engineering Evolved, Tom sits down with Amelia Prasad, Director of Product at Concept to Cloud, to trace how AI has reshaped the day-to-day of UX and product design. Amelia — who came to product from astrophysics and climate science — walks through the shift from manual research, whiteboards and "back-of-the-napkin" sketches to building zero-to-one products directly in Claude Code. It's not a hype reel. Amelia is candid about the friction: learning version control from scratch, bloated six-thousand-line files, the designer-to-developer handoff problem, and the diminishing returns of heavy token usage in tools like Claude Design and third-party wrappers such as Lovable. Her current answer is a marriage of tools — passing work back and forth between Claude Code and Figma via MCP — so prototyping speed and real usability, accessibility and design-system rigour can each live where they belong. They close on what the next 12 months might hold: more human-led user research, not less, and why juniors and design intuition still matter in an industry tempted to hire only senior builders. Chapters 00:00 — Welcome & introducing Amelia 02:53 — From astrophysics to product design 03:33 — The pre-LLM UX workflow: manual research & competitive analysis 05:23 — Old-school tooling: Figma, Miro, Maze, pen & paper 06:56 — The lost art of napkin sketches and paper prototyping 07:57 — Meeting at Princeton: first exposure to LLMs 08:52 — AI workflows before AI building: the interview note-taker 11:02 — Stepping into Claude Code as a non-developer 13:45 — Handing off code on a small team: value and limits 15:17 — Guardrails, context and the handoff problem 20:02 — Lovable, Cursor and the trouble with wrappers 21:05 — Claude Design: token cost and diminishing returns 22:45 — Figma's MCP and the two-way handoff 24:50 — A suite of tools: knowing when to hand off to which 29:06 — Why active engagement in Figma beats waiting on the terminal 33:02 — The next 12 months: user research, systemic processes, robustness 38:16 — Will design jobs disappear? Juniors, intuition & human-in-the-loop 41:27 — Wrap-up & thanks Key takeaways AI adoption in design was gradual — automating admin and research before it could build whole products. The real skill now is orchestration: knowing which tool (Claude Code vs. Figma) does which job best. Speed doesn't replace craft — usability, accessibility and design systems still need a designer's hand. Human intuition and user research grow more important as products become AI-native. Cutting junior roles is short-sighted: today's juniors build the intuition tomorrow's products depend on. Enjoyed this one? Find us at conceptocloud.com and on LinkedIn. Subscribe to Engineering Evolved so you don't miss the next episode.
Episode #16
Private equity firms are facing an unprecedented challenge with a backlog of 13,000 companies. The biggest issue for 2025 isn't raising capital or sourcing deals—it's successfully returning capital to investors after buying at market peaks. Show Notes Episode Overview A concise analysis of the private equity industry's current crisis: managing a backlog of 13,000 companies while struggling to return capital to investors. Key Topics Covered The 13,000-Company Backlog Unprecedented number of portfolio companies awaiting exits Industry-wide challenge affecting firms of all sizes Redefining what success means in private equity The Capital Return Challenge Why returning capital has become the #1 priority for 2025-2026 Shift from traditional metrics of success (fundraising and deal flow) Impact on limited partners and fund performance Market Timing Issues Consequences of buying at market peaks The "top of the bubble" problem Current valuation challenges and exit environment Key Takeaways The private equity industry faces a structural challenge with 13,000 companies in the exit pipeline Capital return has superseded fundraising and deal sourcing as the primary challenge Firms that bought at peak valuations are particularly vulnerable The traditional definition of private equity success is being rewritten Relevant for: Private equity professionals Limited partners and institutional investors M&A advisors and investment bankers CFOs and business owners considering exits Financial market analysts Chapters 0:00 - Introduction: The Private Equity Challenge 0:11 - The 13,000-Company Backlog Crisis 0:19 - Capital Return: The New Priority 0:28 - The Peak Valuation Problem
Episode #15
<p>A technical deep dive into building robust end-to-end tests for podcast publishing pipelines. Learn why scheduled posts are essential for testing without disrupting your content feeds.</p> <p><b>Episode Show Notes</b></p> <p><b>Key Topics Covered</b></p> <p><b>End-to-End Testing for Publishing Pipelines</b></p> Why comprehensive testing matters in content publishing Building reliable automation systems Preventing content delivery failures <p><b>Scheduled Posts as Testing Tools</b></p> Using scheduled content for validation Avoiding feed pollution during testing Maintaining content quality standards <p><b>Synthetic Content in Test Environments</b></p> Best practices...
Episode #14
<p>Engineering leaders learn how the Trio model can eliminate the blame game between business and IT teams. Discover practical strategies for cross-functional collaboration that actually work.</p><p><b>The Trio Model: Breaking Down Business-IT Walls</b></p><p>Key Topics Covered</p><p>The Business-IT Dysfunction Problem</p>Why blame games develop between business and IT teamsThe 'technical purgatory' of mid-sized companies (200-1000 employees)Common symptoms: endless backlogs, shadow IT solutions, demoralized engineers<p>Why Traditional Fixes Fail</p>Hiring more managers: Adds abstraction without contextAdding more engineers: Brooks' Law in actionBetter ticketing systems: Makes misalignment visible but...
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