app01 Sat, 19 Sep 2026 17:35:50 +0000 Fireside (https://fireside.fm) Software Defined Interviews - Episodes Tagged with “Enterprise It” https://www.softwaredefinedinterviews.com/tags/enterprise%20it Thu, 20 Aug 2026 09:00:00 +0200 Deep discussions about technology, enterprise IT, and the like en-us episodic Deep discussions about technology, enterprise IT, and the like Software Defined Talk Deep discussions about technology, enterprise IT, and the like yes Software Defined Talk softwaredefinedinterviews@cote.wtf Episode 125: Running D&D with AI, Determinism First, and Workflow ROI, with Michael Rishi Forrester https://www.softwaredefinedinterviews.com/125 3773701a-4bc5-418d-89fc-1f1c59419585 Thu, 20 Aug 2026 09:00:00 +0200 Software Defined Talk 125 Running D&D with AI, Determinism First, and Workflow ROI, with Michael Rishi Forrester full Software Defined Talk Michael Rishi Forrester built his son a homebrew tabletop campaign with AI in the loop - 20 hours of work instead of 60 to 100 - and found out the hard way that the model had quietly started doing the dice math itself. That turns into an argument about why individuals get so much value out of AI while organizations get so little, and why the ROI is at the workflow level or nowhere. 1:13:29 yes <p>Michael Rishi Forrester does AI workforce transformation at Accenture LearnVantage, after three years at KodeKloud and about thirty years in IT before that. Whitney and Coté talk with him about running tabletop role-playing games with AI. He built his 19-year-old son a homebrew campaign on top of Lancer, the sci-fi mech game, in about 20 hours instead of the 60 to 100 it would have taken him before - and got a website, a virtual tabletop and some Discord bots out of it. What breaks is the interesting part: there was a night when every shot did one damage, because the model had quietly stopped using the dice harness and started doing the math itself.</p> <p>From there it turns into an argument about where AI actually pays off at work. Michael’s position is that the ROI is at the workflow level and there is no organizational ROI to go find, that read-only work over more information than a person can hold is where it currently earns its keep, and that everything he has had success with is a bound system with a finite rule set. Whitney names the through-line: what can be deterministic should be deterministic, and if you need an LLM, scope it tightly and have it write the deterministic thing.</p> <p>It ends on mantis shrimp.</p> <p>You can watch <a href="https://www.youtube.com/watch?v=HRVtMHbIAR0" rel="nofollow noopener">the video version of this episode</a> as well, if you prefer that kind of thing.</p> <p>Mentions:</p> <ul> <li> <a href="https://michaelrishiforrester.com/" rel="nofollow noopener">Michael Rishi Forrester’s home page on the World Wide Web</a>.</li> <li> <a href="https://antiphonthegame.com/" rel="nofollow noopener">Antiphon: The Game</a>, the homebrew Lancer campaign - the whole story, the missions, the board, and the sea-creature capital ships.</li> <li> <a href="https://www.linkedin.com/in/michaelrishiforrester/" rel="nofollow noopener">Michael on LinkedIn</a>, where he posts most often.</li> <li> <a href="https://massifpress.com/lancer" rel="nofollow noopener">Lancer</a>, the sci-fi mech game Antiphon is built on top of. Special Guest: Michael Rishi Forrester.</li> </ul> Michael Rishi Forrester, Accenture LearnVantage, KodeKloud, AI workforce transformation, Dungeons & Dragons, Lancer, Antiphon, solo role-playing, tabletop RPG, application harness, determinism first, deterministic wrappers, MCP, Claude Code, agentic AI, hooks, LLM math, dice rolls, human in the loop, Air Force doctrine, intuition, judgment, enterprise ROI, workflow ROI, bound systems, read-only agents, context management, agent parallelism, alert fatigue, SOC 2 compliance, code review, regulated industries, layoffs, developer productivity, MIT Nanda report, Kubernetes, CI/CD, TDD, platform engineering Michael Rishi Forrester does AI workforce transformation at Accenture LearnVantage, after three years at KodeKloud and about thirty years in IT before that. Whitney and Coté talk with him about running tabletop role-playing games with AI. He built his 19-year-old son a homebrew campaign on top of Lancer, the sci-fi mech game, in about 20 hours instead of the 60 to 100 it would have taken him before - and got a website, a virtual tabletop and some Discord bots out of it. What breaks is the interesting part: there was a night when every shot did one damage, because the model had quietly stopped using the dice harness and started doing the math itself.

From there it turns into an argument about where AI actually pays off at work. Michael’s position is that the ROI is at the workflow level and there is no organizational ROI to go find, that read-only work over more information than a person can hold is where it currently earns its keep, and that everything he has had success with is a bound system with a finite rule set. Whitney names the through-line: what can be deterministic should be deterministic, and if you need an LLM, scope it tightly and have it write the deterministic thing.

It ends on mantis shrimp.

You can watch the video version of this episode as well, if you prefer that kind of thing.

Mentions:

Special Guest: Michael Rishi Forrester.

]]> Michael Rishi Forrester does AI workforce transformation at Accenture LearnVantage, after three years at KodeKloud and about thirty years in IT before that. Whitney and Coté talk with him about running tabletop role-playing games with AI. He built his 19-year-old son a homebrew campaign on top of Lancer, the sci-fi mech game, in about 20 hours instead of the 60 to 100 it would have taken him before - and got a website, a virtual tabletop and some Discord bots out of it. What breaks is the interesting part: there was a night when every shot did one damage, because the model had quietly stopped using the dice harness and started doing the math itself.

From there it turns into an argument about where AI actually pays off at work. Michael’s position is that the ROI is at the workflow level and there is no organizational ROI to go find, that read-only work over more information than a person can hold is where it currently earns its keep, and that everything he has had success with is a bound system with a finite rule set. Whitney names the through-line: what can be deterministic should be deterministic, and if you need an LLM, scope it tightly and have it write the deterministic thing.

It ends on mantis shrimp.

You can watch the video version of this episode as well, if you prefer that kind of thing.

Mentions:

Special Guest: Michael Rishi Forrester.

]]> Episode 124: The Chief Therapy Officer, Job Titles as Culture Change, and AI as Spreadsheets, with Bryan Ross https://www.softwaredefinedinterviews.com/124 a4a2167f-2cb9-4f13-af10-067073382ca9 Wed, 05 Aug 2026 11:00:00 +0200 Software Defined Talk 124 The Chief Therapy Officer, Job Titles as Culture Change, and AI as Spreadsheets, with Bryan Ross full Software Defined Talk 1:09:48 yes <p>Bryan Ross is a Field CTO at GitLab, a role he describes as straddling sales, customer success, and solution architecture - or, as one of his customers renamed it, chief therapy officer, which he has since turned into a Substack. Whitney and Coté talk with him about what the job actually looks like: getting catapulted into an account by the sales team, asking a lot of questions, and finding out about four minutes in that the tech problem is a human one. He makes the case that changing job titles - sysadmin, DevOps engineer, platform engineer, now context engineer - is mostly an organization trying to change its culture without knowing how, and that the real difference is mindset: keeping a box alive versus serving one team versus building a product. There’s a long stretch on metrics, including Goodhart’s law, why every metric needs a balancing one, and why he cared more about how many VMs were being decommissioned than how many were being provisioned. Also: whether anyone actually needs to ship faster (Coté’s pharmacy doesn’t), the UK Postal Service discovering that a friendly postman beat a modernized delivery fleet on customer satisfaction, and why copying Google is usually the wrong move. On AI, Bryan’s argument is that it will end up like spreadsheets - a few experts building the macros, everyone else using and lightly tinkering with what they made - and that which model you use should be a finance and data governance decision, not a developer one. Plus the hazard of a nicely formatted report: the pastel-shading trick for spreadsheets nobody will check, and why an AI scoring something 6 out of 10 gets the same unearned benefit of the doubt.</p> <p>Also, ordering pizza in Amsterdam.</p> <p>You can watch <a href="https://www.youtube.com/watch?v=w184M4RtlIU" rel="nofollow noopener">the video version of this episode</a> as well, if you prefer that kind of thing.</p> <p>Mentions:</p> <ul> <li> <a href="https://bryanross.me/" rel="nofollow noopener">Bryan Ross’s home page on the World Wide Web</a>, which links to everything else.</li> <li> <a href="https://chieftherapyofficer.co.uk/" rel="nofollow noopener">Chief Therapy Officer</a>, Bryan’s Substack.</li> <li> <a href="https://www.linkedin.com/in/bryanross/" rel="nofollow noopener">Bryan on LinkedIn</a>.</li> <li> Coté's <a href="https://cote.pizza/shit-people-say/" rel="nofollow noopener">list of "laws," anecdotes, and common shit people say</a>. See also <a href="https://hacker-laws.com/" rel="nofollow noopener">Hacker Laws</a>. Special Guest: Bryan Ross.</li> </ul> Bryan Ross, GitLab, field CTO, chief therapy officer, platform engineering, DevOps engineer, job titles, sysadmin, context engineer, Goodhart’s law, metrics, balancing metrics, VM provisioning, decommissioning, repaving, microservices, monolith, LAMP stack, Kubernetes, golden paths, developer velocity, shipping faster, UK Postal Service, customer satisfaction, AI adoption, frontier models, model routing, FinOps for AI, agentic engineering, diffusion of innovations, Conway’s law, non-determinism, CI, coding agents, AI evaluation, tool sprawl, Jenkins, Tanzu, Substack, The New Stack Bryan Ross is a Field CTO at GitLab, a role he describes as straddling sales, customer success, and solution architecture - or, as one of his customers renamed it, chief therapy officer, which he has since turned into a Substack. Whitney and Coté talk with him about what the job actually looks like: getting catapulted into an account by the sales team, asking a lot of questions, and finding out about four minutes in that the tech problem is a human one. He makes the case that changing job titles - sysadmin, DevOps engineer, platform engineer, now context engineer - is mostly an organization trying to change its culture without knowing how, and that the real difference is mindset: keeping a box alive versus serving one team versus building a product. There’s a long stretch on metrics, including Goodhart’s law, why every metric needs a balancing one, and why he cared more about how many VMs were being decommissioned than how many were being provisioned. Also: whether anyone actually needs to ship faster (Coté’s pharmacy doesn’t), the UK Postal Service discovering that a friendly postman beat a modernized delivery fleet on customer satisfaction, and why copying Google is usually the wrong move. On AI, Bryan’s argument is that it will end up like spreadsheets - a few experts building the macros, everyone else using and lightly tinkering with what they made - and that which model you use should be a finance and data governance decision, not a developer one. Plus the hazard of a nicely formatted report: the pastel-shading trick for spreadsheets nobody will check, and why an AI scoring something 6 out of 10 gets the same unearned benefit of the doubt.

Also, ordering pizza in Amsterdam.

You can watch the video version of this episode as well, if you prefer that kind of thing.

Mentions:

Special Guest: Bryan Ross.

]]> Bryan Ross is a Field CTO at GitLab, a role he describes as straddling sales, customer success, and solution architecture - or, as one of his customers renamed it, chief therapy officer, which he has since turned into a Substack. Whitney and Coté talk with him about what the job actually looks like: getting catapulted into an account by the sales team, asking a lot of questions, and finding out about four minutes in that the tech problem is a human one. He makes the case that changing job titles - sysadmin, DevOps engineer, platform engineer, now context engineer - is mostly an organization trying to change its culture without knowing how, and that the real difference is mindset: keeping a box alive versus serving one team versus building a product. There’s a long stretch on metrics, including Goodhart’s law, why every metric needs a balancing one, and why he cared more about how many VMs were being decommissioned than how many were being provisioned. Also: whether anyone actually needs to ship faster (Coté’s pharmacy doesn’t), the UK Postal Service discovering that a friendly postman beat a modernized delivery fleet on customer satisfaction, and why copying Google is usually the wrong move. On AI, Bryan’s argument is that it will end up like spreadsheets - a few experts building the macros, everyone else using and lightly tinkering with what they made - and that which model you use should be a finance and data governance decision, not a developer one. Plus the hazard of a nicely formatted report: the pastel-shading trick for spreadsheets nobody will check, and why an AI scoring something 6 out of 10 gets the same unearned benefit of the doubt.

Also, ordering pizza in Amsterdam.

You can watch the video version of this episode as well, if you prefer that kind of thing.

Mentions:

Special Guest: Bryan Ross.

]]>