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Eric Lamanna
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Software and AI development podcast. We cover all things software development, including today's advanced AI development tricks and techniques.

  1. hace 1 h

    Why Your Status Report Gets Ignored (And How to Fix It)

    Status reports are one of the most time-consuming recurring deliverables in project management — and one of the most reliably ignored. This episode of Development digs into why that happens and, more usefully, what project managers can do about it before the next report goes out. The root cause isn't effort or data quality; it's a structural mismatch between how PMs narrate progress and how executives actually consume information. The episode walks through a concrete, principle-by-principle rewrite of the typical status report, covering: The three questions every executive is actually asking — and why most reports never answer them directly or quickly enough Leading with the signal, not the story — how to open with a declared status (green/amber/red) followed immediately by the one or two sentences that justify it Surfacing decisions early and explicitly — why a dedicated "decisions needed" section near the top of the report does more for executive engagement than any design improvement Filtering the risk section ruthlessly — distinguishing between risks that belong in the RAID log and the smaller set that are live enough to appear in this week's update Adding a forward look — a brief preview of the next cycle's key milestones that turns reporting into a governance partnership rather than a formality; teams investing in executive reporting practices consistently see stronger stakeholder alignment A worked hypothetical — a system migration scenario that illustrates exactly how the same three pieces of information read completely differently when reordered around the reader's priorities The episode is clear that none of this requires a new tool or a ground-up template redesign. Every principle discussed can be applied to whatever format a team is already using. For project managers who want a ready-made structure that reflects how real stakeholders read updates, the weekly status report template on ProjectManager offers a practical starting point built around stakeholder-first reporting. Listeners who want to go deeper on the AI angle of status reporting should also check out automated status reports as a complement to the structural principles covered here. More from the show: if this episode got you thinking about how language and instruction shape project outcomes, the earlier episode Prompt Is Policy: Writing AI Instructions Like You Mean It is a natural follow-on. ProjectManager RFP

  2. hace 1 día

    Prompt Is Policy: Writing AI Instructions Like You Mean It

    System prompts are the invisible policy layer inside every AI tool your business runs — and most of them are written like rough drafts rather than operational documents. This episode of Development tackles a failure pattern that founders and ops teams hit repeatedly: an internal tool that performs well in testing collapses into inconsistency the moment real users, real inputs, and real edge cases arrive. The fix isn't technical. It's in how the prompt is written. The episode walks through four concrete principles for writing system prompts that hold their shape under pressure, covering: Job, scope, and edge — all three. Most prompts define what an agent should do but skip what it shouldn't, and what it should do when it hits a situation outside its lane. All three elements are required to write an actual policy rather than a job description. Worked examples inside the prompt. Abstract rules leave room for interpretation; concrete examples of both a clean output and a correctly handled ambiguous case communicate in ways that instructions alone cannot. This is one of the most underused techniques in custom internal tools. Explicit failure-mode handling. Every agent has predictable failure modes — the complaint arriving through an intake form, the brief missing a budget, the transcript with no decisions. Listing the five most likely off-path inputs before launch and writing handling instructions for each is a stress test you run before your users do it for you. Version-controlling prompts like code. A system prompt is a policy document and should have a change history. When an agent's behavior shifts unexpectedly, the first question is always what changed — and without a version log, that question is unanswerable. A full worked example. The episode contrasts a vague vendor-inquiry prompt with a policy-grade version, showing how roughly twenty additional minutes of writing translates into meaningfully more reliable behavior at volume. The broader argument is that when you build on top of a language model — rather than renting off-the-shelf software — you own the consistency problem. Prompt-as-policy thinking is how teams building workflow automation or standing up AI employees inside their operations keep that consistency from eroding over time. For more on this episode's themes, the show previously explored related decision-making in How to Read an Evaluation Criteria Section Before You Write a Word. VB RFP

  3. hace 2 días

    How to Read an Evaluation Criteria Section Before You Write a Word

    Evaluation criteria are the closest thing a solicitation offers to an answer key — yet most proposal teams treat them as an afterthought. This episode of Development makes the case for flipping that habit entirely: reading the evaluation criteria section first, reading it slowly, and letting it drive every structural decision before the writing begins. The difference between a technically compliant proposal and a winning one often comes down to whether the team understood what was actually being scored. The episode walks through a four-step framework for getting full value out of an evaluation criteria section, covering: Factor order and weight — understanding that agencies publish their scoring priorities explicitly, and that page count, narrative depth, and writer assignment should all follow that hierarchy. Sub-factor mapping — going one level deeper to identify every grading dimension under each major factor, and ensuring the proposal addresses each one explicitly and separately. Reading between the lines — recognizing that the structure of the evaluation criteria often encodes the agency's real anxieties, such as transition risk or key personnel stability, even when those concerns aren't stated outright. Rating scale definitions — finding and using adjectival or numerical scoring definitions to understand exactly what separates an "Outstanding" from a "Good," and writing deliberately to the higher threshold when it's achievable. The evidence-and-differentiator matrix — a pre-writing exercise that forces teams to confirm, for every sub-factor, what proof they have and why their approach beats a reasonable competitor's before outlining begins. Proposal architecture — aligning the table of contents and section depth to mirror the evaluator's scoring sheet, so the document speaks the same language as the review panel. A worked example using a managed IT services solicitation shows how these steps play out in practice — from allocating narrative weight across factors to separating relevance and quality arguments within a past performance section. For teams preparing to build a structured compliance matrix against evaluation factors rather than just requirements, building a compliance matrix offers a practitioner-level walkthrough of the mechanics. Tools like document intelligence can also help surface evaluation language and structure it for faster analysis during the pre-write phase. And for those still deciding whether a given opportunity is worth the effort, go/no-go scoring brings the same evaluator-facing discipline to the pursuit decision itself. More from the show: listen to From Prototype to Production: How Low-Code Is Changing the Build for a different angle on how teams are accelerating their workflows. RFP

  4. hace 3 días

    From Prototype to Production: How Low-Code Is Changing the Build

    Low-code development has moved well past the hype cycle — nearly 40% of businesses are now deploying it outside of IT, and the reasons why are hard to argue with. This episode of Development takes a ground-level look at what building in a low-code environment actually involves, drawing on this deep-dive on moving from prototype to production with low-code. Rather than rehashing the sales pitch, the episode maps out the real mechanics, the meaningful trade-offs, and the decision criteria teams should be using before they commit to a platform. Here's what the episode covers: Low-code vs. no-code — a distinction that matters: Low-code reduces the volume of manual coding, but it still demands technical thinking — understanding APIs, integrations, and UI design principles. It's not a shortcut for non-developers; it's a force multiplier for those who know what they're doing. Why prototyping is where low-code earns its reputation: The modular, component-based nature of these platforms can compress a prototype from weeks to days — accelerating the build-test-learn cycle that sits at the core of agile development. How production-readiness is increasingly built in: Iterative development, integrated security (rather than bolted-on afterthoughts), and standard performance monitoring tools are making the prototype-to-production transition smoother than it's ever been. Where low-code falls short: Applications with demanding security requirements, strict accessibility standards, or extreme performance-at-scale needs may require hand-coded solutions — pre-generated code has real ceilings, and the episode is direct about where they are. The best-fit use cases: Simple mobile apps, customer self-service portals, online communities, and industry-specific tools in finance, healthcare, logistics, and education are all strong candidates — and the episode explains why each one fits. Five best practices for teams using low-code well: Master the platform deeply, release frequently, take UX seriously, reserve custom code for what truly differentiates the product, and never underestimate the value of experienced developers just because the tooling is visual. The episode also walks through how to approach platform selection — aligning choices with specific goals like speed to market, cost reduction, or security posture — and makes the case for bringing in specialists when the decision feels unclear. More from the show: if you're thinking about infrastructure and scale, don't miss Static Residential Proxies: Stability, Scale, and Stealth at Trillion-IP Scale, which explores what it takes to operate at extreme network volume. DEV RFP

  5. hace 4 días

    Static Residential Proxies: Stability, Scale, and Stealth at Trillion-IP Scale

    Blocked requests, CAPTCHA walls, and mid-session re-verification aren't just nuisances — they're symptoms of a mismatched infrastructure choice. This episode of Development makes the case that for data operations requiring session continuity, geographic authenticity, and high trust scores, static residential proxies aren't just a preference; they're the correct tool. The discussion draws on the in-depth static residential proxy guide published by Search.co, which runs one of the more comprehensive proxy and data extraction stacks available today. The episode works through the full landscape — from the basics of how proxies route traffic, to why datacenter IPs are so easily flagged, to the specific niche that static residential addresses fill that rotating proxies simply can't. Here's what's covered: Datacenter vs. residential vs. static residential: A clear breakdown of why websites treat these IP types so differently, and what "trust score" actually means in practice. The rotation problem: Why rotating residential proxies, despite their scale advantages, become a liability the moment your operation needs account logins, session consistency, or the appearance of a single returning user. Trillion-IP scale explained: What it means to have access to both IPv4 and IPv6 static residential addresses in the trillions — and why geographic diversity and protocol coverage matter for enterprise-level operations. High-value use cases: Market research, SEO rank tracking, ad verification, e-commerce intelligence, and social media account management — each mapped to the specific reason IP persistence makes or breaks the workflow. Teams building serious data scraping infrastructure will find these distinctions immediately actionable. Matching IP type to task: A use-case-first framework for deciding when static residential is the right call versus when rotating or datacenter proxies are more cost-efficient — with sub-50ms latency and legitimate ISP sourcing flagged as the benchmarks worth holding vendors to. The IPv6 transition: Why access to static residential addresses across both protocols is increasingly important as more platforms shift their infrastructure away from IPv4-only environments. The broader argument the episode makes is that data access is an infrastructure problem, and the right answer depends on whether your operation needs continuity or volume. For teams that need to look like the same authenticated user, in the same location, over time — static residential is the answer. For raw, stateless volume, rotation may win on cost. The episode closes with a practical prompt: start with your use case, then work backward to the IP strategy. For teams also thinking about downstream analysis of the data they collect, AI data analysis tooling can extend what's possible once the pipeline is reliably feeding clean inputs. More from the show: if you're thinking about infrastructure and competitive positioning from a different angle, the episode What Private Equity Really Looks for in Manufacturing Acquisitions offers a sharp look at how operators assess and build durable business advantages. Search RFP

  6. hace 5 días

    What Private Equity Really Looks for in Manufacturing Acquisitions

    When private equity comes knocking on a manufacturing company's door, the evaluation has often already begun long before the site visit. This episode of Development pulls back the curtain on the criteria deal teams actually use — the strategic filters, financial thresholds, and operational tells that separate a compelling acquisition target from a pass. Drawing on this in-depth look at PE acquisition criteria for manufacturers, the episode gives owner-operators a clear-eyed view of what the investment committee scorecard really looks like. Here's what the episode covers: Platform vs. add-on classification — how deal teams label a target in the first hour, and why that decision shapes valuation, deal structure, and everything in the investment memo. Market tailwinds and fragmentation — why investors chase sectors with 5%+ CAGRs and unconsolidated competitive landscapes, and how to position your business inside those narratives compellingly. Competitive moats — what actually counts as a defensible advantage (proprietary tooling, sole-source OEM status, painful switching costs) versus what gets discounted as a personal relationship with one customer. Revenue quality and EBITDA translation — the difference between recurring supply agreements and job-shop volatility, why 70%+ EBITDA-to-free-cash-flow conversion puts a target in a different conversation, and the working capital metrics investors benchmark against peer medians. Manufacturers investing in workflow automation are increasingly well-positioned here, as tighter processes directly support cleaner cash conversion. Operational signals on the floor — what walk-throughs actually reveal: shadow boards, andon lights, process capability indices above 1.33, and whether tribal knowledge is documented or locked in one machinist's head. Leadership bench strength — why a founder-dependent business triggers escrow provisions and retention carve-outs, and what a credible depth chart looks like to an investor modeling a five-year hold. Manufacturers using production dashboards to surface real-time operational data give leadership teams the visibility PE firms want to see baked into daily management. The episode also addresses supply chain diligence — country-of-origin concentrations, dual-sourcing plans, and vendor scorecards — as a now-standard part of competitive auctions. The full source article, frameworks, and threshold data are at Manufacturing.co. For more on how AI decision-making intersects with operational strategy, check out the Development episode The Handoff Trap: Designing AI Agents That Know When to Stop. Manufacturing RFP

  7. hace 6 días

    The Handoff Trap: Designing AI Agents That Know When to Stop

    Shipping an AI agent that works perfectly in testing is one thing — designing one that knows when to pause and hand control back to a human is something else entirely. This episode of Development tackles one of the most overlooked problems in AI agent design: the handoff trap, the moment when an agent keeps going exactly as instructed and that turns out to be the problem. Far from a niche edge case, this is a core architectural decision that determines how much trust and autonomy a business can safely give its automation. The episode walks through a practical framework for building intentional, well-designed handoffs — covering three distinct trigger categories and the design principles behind each: Ambiguity in the input — not just "is this unclear?" but whether the ambiguity affects the outcome in a way that matters, with real examples showing why confidence scores miss what plain-language business rules catch. Irreversibility in the action — why every consequential action should pass a simple undo test, and how a staging layer lets agents run at full speed on most volume while still protecting high-stakes decisions. Scope creep in the task — how agents wander past their task boundary and why a "flag and wait" response turns unexpected findings into actionable intelligence rather than unauthorized decisions. Autonomy as a spectrum — the core principle that better-designed handoffs enable more autonomy everywhere else, not less; the two are complementary, not in conflict. The human-side experience — why a poorly designed escalation UI destroys the whole system through reviewer fatigue, and what a well-structured handoff information package looks like. A practical starting exercise — a concrete, this-week action for mapping irreversible actions, ambiguous inputs, and boundary-crossing moments into a plain-language handoff specification. This design philosophy sits at the heart of how workflow automation is built to last — and it's directly relevant to anyone exploring AI employees as part of their operations. For more on the build process and how these principles apply in practice, how the build process works is a good place to start. More from the show: listen to How to Write a Past-Performance Entry That Actually Wins Points for another episode on turning process discipline into real operational results. VB RFP

  8. 14 ago

    How to Write a Past-Performance Entry That Actually Wins Points

    Past performance is one of the highest-stakes sections in any competitive proposal, yet it's routinely assembled at the last minute from whatever scraps a shared drive happens to hold. This episode of Development takes a practitioner-level look at why that approach consistently loses points — and what a deliberate, infrastructure-first strategy looks like instead. The focus is on specificity: what a winning entry actually contains, why evaluators score the way they do, and how to build a library that lets your team pull a polished, relevant entry in hours rather than days. Here's what the episode covers: How evaluators actually score past performance — relevance is assessed along two axes (scope and complexity), and narratives that don't explicitly address both leave evaluators with nothing to credit. Leading with the parallel, not the summary — the most effective entries open by connecting the completed work directly to the current requirement, before any administrative detail appears. Specificity over generality — vague phrases like "delivered on time" are invisible on a scoring form; concrete, outcome-shaped claims about real problems solved are not. What a well-built library entry contains — contract facts, a pre-written relevance mapping, specific outcomes, customer voice (quotes and paraphrases from reviews or award letters), and verified reference contact information. Writing entries at capture time, not proposal time — the window right after contract closeout, while details are fresh and customers still take your calls, is when the most valuable intelligence can be gathered. Managing reference relationships and entry age — tracking lookback windows, maintaining customer relationships between awards, and auditing references before they go cold are all part of keeping the library genuinely useful. Teams working inside response automation workflows will find this episode particularly relevant — a structured past-performance library is the raw material that makes automated assembly accurate rather than generic. If your team is still deciding which opportunities are worth this level of investment, go/no-go scoring can help focus your capture energy where past-performance strength is already strongest. For deeper reading on proposal structure and compliance, proposal templates from RFP.co offer practical starting points aligned with evaluator expectations. For more on the tools that can reclaim time during response, check out the episode Document Automation Software: 20 Platforms That Could Win Back Your Time. RFP

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Software and AI development podcast. We cover all things software development, including today's advanced AI development tricks and techniques.

Información

  • Creador
    Eric Lamanna
  • Años de actividad
    2026
  • Episodios
    80
  • Clasificación
    Apto
  • Copyright
    © 2026 DEV.co
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