Playback focuses on discussing tech advancements, trends, deployment strategies, certification best practices, and news around the OTT and streaming industry.
AI-Assisted Development Looks Easy, That's the Problem - ft. Daniel Eneström and Daniel Astudillo
In this episode of the Accedo Playback Podcast, we had a chat with Daniel Eneström, Head of Engineering for Europe and Latin America, and Daniel Astudillo, Head of Engineering for North America, to discuss the impact of AI on the streaming software industry, focusing on engineering challenges, expertise, and the evolving development landscape.
AI has significantly lowered the barrier to building streaming software, allowing the first 80% of a project to be completed quickly. However, this comes with real costs: more security vulnerabilities, more code duplication, and engineers who understand less of what they've actually shipped.
The conversation turns on what closes the remaining 20%: judgment built from hundreds of deployments, the kind that knows how systems fail together during a live event or why a phone experience needs different decisions than a living room one.
Our guests also dive deep into the actual practices: managing shared context across teams and agents, what makes an effective agent harness, and why a hybrid of frontier and open-source models is likely where the industry lands as token costs rise.
Topic discussed
01:10 What's actually changed in AI-assisted development over the last two years
02:28 Every team reaches the same 80% — and why that's no longer the differentiator
05:32 The hidden cost of AI-assisted code: longer PRs, slower reviews, lower comprehension
09:36 What "accumulated expertise earned over hundreds of deployments" means in practice
13:04 Managing shared context across teams and AI agents at scale
18:04 Building an effective agent harness: why inputs are king
22:05 Frontier models vs. open-source tooling, and the case for a hybrid approach
26:00 Is genuine differentiation still possible once AI raises everyone's floor?
29:20 The one question technical leaders should be asking but usually aren't
10 Aug 2026
The Composability Gap: What Stands Between Streaming and AI, ft. Remon Fahim and Fredrik Anderson.
In this episode of the Accedo Playback Podcast, Remon Fahim (https://www.linkedin.com/in/remonfahim/), Founder and Managing Director of Remon Consulting/ CFO at Creative Access and Fredrik Anderson (https://www.linkedin.com/in/accedofredrik/), Co-Founder of Accedo, join host Bleuenn Le Goffic (https://www.linkedin.com/in/bleuenn-le-goffic-72553014/?locale=en), Accedo's VP Business Transformation to tackle a question every media executive is wrestling with: how do you actually decide what's worth investing in when everyone's chasing AI, but almost no one can prove the return?
For years, the execution strategy behind a technology investment was less of an issue than the debate of build versus buy, or how to differentiate. Now with AI, things changed and the investment decision itself is the hard part.
This episode's conversation traces why: a wave of "demand sophistication" has made products and solutions far more complex, product and engineering teams are struggling to translate that complexity into a business case a CFO can actually sign off on, and the pressure to move — driven as much by fear of falling behind as by any clear ROI — is pushing companies to invest before they've defined what outcome they're even chasing.
Timeline
00:10 Introduction: the AI investment decision is what executives can't confidently make.
05:40 Is it harder for a CFO to sign off on AI investments than it used to be?
09:36 Is the sheer number of new tech possibilities making the outcome analysis shallower?
13:35 Is there a "readiness" fast-track companies need before AI investment even makes sense?
16:44 Are strategy and execution really two separate problems, or the same one?
21:50 Do CFOs need to fundamentally change how they evaluate the business case itself?
26:05 Should companies rethink their whole platform, or focus on smaller automations?
31:12 What's the first question a CPO should ask about their own platform's composability?
33:29 What should CFOs be challenging product and engineering teams to answer?
36:44 What should people actually be looking for at IBC 2026?
17 Jun 2026
The Last Mile: Where AI Stops and Expertise Begins in Streaming, with Michael Chan and Edit Kovacs
How far can AI actually take you in a running streaming service?
In this episode, Accedo's Edit Kovacs, VP of Europe and Latin America, and Michael Chan, VP of Operations North America, make the case for forward deployed engineering in the AI era.
While AI has made the first 80% faster than ever, the last mile, the challenges from device fragmentation, DRM compliance, recommendation engines that need continuous care, and still demands something no model can provide: engineers with deep domain knowledge and enough scar tissue to know what breaks in production and why.
The build-and-handover model is no longer fit for purpose. The future belongs to long-term embedded partnerships focused on continuous operation, evolution, and outcomes.
Timeline:
01:15 What is forward deployed engineering and why now?
04:15 Why AI has shifted the bottleneck from models to implementation
05:32 The last mile problem in complex streaming environments
08:50 Device fragmentation and the ceiling AI can't lower
11:30 How AI changes the relationship between client and tech partner
17:18 Maintaining context in long-term embedded engagements
21:34 Domain expertise, regional compliance and the 20% that matters
28:40 The future of FDE: from building to governing agentic workflows
Reach and audience
Public platform figures. Ratings count people who left a rating, not total listeners.
YouTube views
146,592
Score snapshot 15 Sept 2025
Spotify
4.8 / 5
5 ratings
Podcast Authority Score: 59 / 100
A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.
Quality
61
Social presence
0
YouTube
82
Engagement
60
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