13) Tobias K. Torrissen om kodekvalitet, konferanser og AI

Truls Jørgensen og Audun Fauchald Strand — Heis Podcast · podcast · 2026-03-16 source ↗ Reader 🖥️

Agent Harness AI as Amplifier Architecture Decision Records Code Quality Craft Community Public-Sector Digitalization Software Design Fundamentals Technology Leadership (Heis)Vibe Coding

In the age of LLM-generated code, the durable value of an engineering leader is not in writing code but in cultivating the engineering practices, explicit design discipline, and craft community that determine whether a long-lived system can be understood, maintained, and adapted — and code quality, understood as 'obvious over clever,' matters more in this era, not less.

practical · mixed — A conversation that mixes narrative (JavaZone origins, NAV quality reviews, son who vibecodes apps), expository reflection (his three-camp taxonomy of AI coders, his definition of architecture's purpose), and prescriptive practical argument (juniors should learn fundamentals before AI tools; teams should double down on engineering practices in the AI era; KS processes should leave more room for product thinking). The overall thrust is action-guiding: how should an engineering leader, junior, or team behave now that code is cheap to generate.

Structure

Part	Role
Introduction: Torrissen's career arc — Skatteetaten, Scienta consultancy leadership, role in early JavaZone, JavaBin board, Dataforeningen	Establishes Torrissen's authority as a fagperson-leder hybrid: someone who leads consultants but is grounded in the craft and in community-building over two decades
JavaZone origin narrative: Roots conference Bergen (Cockburn, Fowler), early program committee, growth from 200 → spectrum-scale, the 'we thought we did not have to pay VAT' war story, Sun Microsystems bailout	Narrative evidence for the thesis that fagmiljø (craft community) is formative — Torrissen attributes his career direction to a single lunch at Roots
KS1/KS2 process explanation and Torrissen's role as IT-alibi for Finansdepartementet	Context: explains the institutional setting of his code-quality reviews and why he reluctantly stays in a process he is partially critical of
NAV code-quality review methodology and findings — sit down with developers, talk architecture, no traffic-light report, 'voksenopplæring' for leadership	Practical exemplar of his reviewing philosophy: not revision, not grading, but facilitated reflection that surfaces what developers already know
Architecture critique: 'everyone wants microservices, Kotlin, event sourcing' — Sykepenger as a case where koreografert/event-driven was chosen but the underlying domain (forvaltningsloven) is stable and may not require that flexibility	Concrete extended example of his core claim that architecture must underbygge virksomhetens mål, not follow fashion
Microservices as 'architecture of last resort' — Parnas-style law of distribution (don't, don't yet, do if expert), Vlad Khononov's 'Balancing Coupling'	Theoretical scaffolding: invoking design laws and recent literature to ground the skepticism
Audun's pushback: monolith (KOS) was unmaintainable, microservices are sosial skalering — domain isolation in-process keeps failing because humans don't respect non-enforced boundaries	Counter-position. The episode lets this stand; Torrissen does not concede but the disagreement is named
Three-camp taxonomy of developers in the AI era: (1) head-in-sand, (2) harness LLM into quality engineering, (3) vibecoders / large-scale agentic parallel work	Central conceptual contribution. Names the design space and positions himself in camp 2
Engineering practices that matter more under AI: fast feedback loops, observability, frequent delivery, learning-oriented methodology — citing a TET (Telenor?) talk on Claude adoption	Evidence: teams with good practices get a productivity step-up from AI; teams without amplify chaos
Reflection on explicitness: 'I used to design by intuition; now I have to tell the language model.' Architecture Decision Records as fosilitering of process	Mechanism: why AI sharpens design discipline — it forces what was tacit into text
Aesthetic concession: classical code-quality metrics (cyclomatic complexity, method length) matter less now; 'beautiful code' may be receding as a craft value; 'obvious over clever' (NAV's tekniske retning) is what survives	Calibration: not everything from old code-quality discourse carries forward; some loss is real
Quality-vs-context: timeføring system vs. NAV sykepenger vs. politiet straffesak — different systems warrant different quality bars; AI lowers the entry threshold for low-stakes software, market for software grows	Qualification: quality is not monotonic. Different software 'modes' (reference to Heinemeier Hansson?) warrant different bars
Will developers be unemployed? Only ~20% of system development is programming; cheaper software grows the market; long-tail bespoke software (the frisørkjede booking system) becomes economic	Counter-pessimism argument. Hands-off industry forecast
Advice to juniors: learn IT architecture and core principles before climbing into the 'Formula 1 car' of language models — 'drive a Toyota Corolla first'; TDD from 2004 still relevant; dora.dev	Pedagogical conclusion: fundamentals first
Conferences as formative: Roots Bergen as career-defining; JavaZone, Booster, Kodemaker fagdag, Kode24-dagen as ongoing fagmiljø; JavaZone's real success is generational continuity	Closing return to the opening — community as the lifelong infrastructure for craft

Key terms

kodekvalitet (code quality) Code Quality
Not classical metrics (cyclomatic complexity, coupling, method length) but: obviousness over cleverness, readability, deletability, fitness-for-purpose for the system's actual mode (long-lived regulated software vs. throwaway). Quality is defined by whether the team — '70 forvaltere' of varying ambition and life-balance — can collectively own and evolve the code over 30 years.
obvious, ikke clever Software Design Fundamentals
A design heuristic: prefer code that is immediately understandable to a new reader over code that is compact, elegant, or sophisticated. Few abstractions, explicit over implicit.
tilført vs. essensiell kompleksitet Software Design Fundamentals
Borrowed Brooks/Moseley-Marks framing: essential complexity is inherent to the domain (you can move it but not destroy it); accidental/added complexity is what design discipline can remove. The job is minimising added complexity so only essential remains.
engineering-praksiser
A bundle: fast feedback loops, observability, frequent delivery, learning-oriented work methodology, TDD, architecture decision records, pair/team design discussion. Practices that produce 'bevissthet rundt hvordan du utvikler software'.
harnesse (en språkmodell) Agent Harness
To wrap and constrain a language model so it produces code of quality matching the team's standards — explicit design context, ADRs, practices, observable feedback. Camp 2 in the taxonomy.
vibecoding Vibe Coding
Used loosely. He distinguishes: (a) his son spying out apps from home for ad revenue — kortsiktig, kjapt, deretter — which he calls his personal meaning; (b) the more serious 'on-to-pi-tenakt' parallel-agentic large-scale development that doesn't engage with code as an abstraction. He hints these are conflated in discourse.
fagmiljø / community Craft Community
A self-organising volunteer-driven craft community (JavaBin, JavaZone, Booster, Kodemaker fagdag) that produces formative encounters and intergenerational transmission of practice. He attributes his career to such encounters.
Architecture Decision Records (ADR) Architecture Decision Records
Less important for sporbarhet than for facilitating a fornuftig prosess where team perspectives are aired. The act of producing them is the value, not the artifact.
KS1 / KS2 Public-Sector Digitalization
Norwegian state-investment quality-assurance gates (concept choice; project pre-realisation plan). He criticises them for over-quantifying targets early and locking in goals that learning will outdate, but works inside them to nudge toward smidig/produktutvikling.
voksenopplæring
What his code-quality reviews actually deliver to client leadership instead of the requested traffic-light verdict: adult education in what their developers know and what tradeoffs they face.
goldplating Software Design Fundamentals
The product-development failure mode where teams over-invest in first-iteration polish because tight user feedback creates over-identification with the user's wants. He has a høne to plukke with product-utviklingsmiljø about this.
obvious-rapport / tilrådninger (ikke terningskast)
His review output: a map of choices made and why, plus directional recommendations (more/less distributed, focus more on technical debt) — explicitly not a score.

Propositions

explicitCode quality matters more in the AI era, not less.conf: high
explicitThe right yardstick for code quality is whether ~70 long-tenured maintainers — across a 30-year average lifespan for state systems — can collectively understand and evolve the code; 'obvious' beats 'clever'.conf: high
explicitClassical code-quality metrics (cyclomatic complexity, method/class length, coupling, cohesion) are largely irrelevant to whether a code-quality review surfaces what matters; they are not where it skorter.conf: high
explicitAesthetic 'beautiful code' as a craft value is receding; when machines do more of the writing, prettiness matters less than readability and ownership.conf: high
explicitThere are three current camps of developers regarding AI: (1) those who refuse to engage, (2) those who harness LLMs into quality-engineering workflows, (3) those who run large-scale parallel agentic work without engaging with code as an abstraction.conf: high
explicitTeams with good engineering practices (fast feedback, observability, frequent delivery) get a steep productivity step-up from AI; teams without amplify their existing chaos.conf: high
explicitAI raises the value of explicit, articulated design — what used to be tacit intuition must now be written down so the language model can act on it.conf: high
explicitArchitecture should under-build the business's actual goals, not follow industry fashion; the fact that 'every customer in Norway has the same goals' (microservices, Kotlin, event sourcing) is a red flag.conf: high
explicitdevelopedMicroservices are 'an architecture of last resort'; teams move to them too quickly, hiding global complexity in local-simplicity-per-service.conf: high
extends ←SWLW #710: Revised rules of Eng Leadership, When AI costs more than the engineer, and more. · p9 — Kokane applies the 'microservices are an architecture of last resort; teams adopt them too fast' caution to agentic loops — same over-adoption critique, new abstraction.
explicitdevelopedMicroservices may nonetheless be justified for social scaling — letting many people work on one problem — because in-process domain boundaries keep failing in practice.conf: high
refines ←Article: Modular Edge Computing at Multi-Tenant SaaS Scale on Cloudflare Workers · p3 — Refines Torrissen/Audun's 'social scaling' justification for microservices with the operational precondition their debate never named (per heis-13#g2): decomposition escapes 'last resort' status specifically once the platform offers a same-process/same-machine call primitive that removes the network-hop tax — otherwise that same tax is what makes premature splitting a last resort in the first place.
explicitThe value of an external code-quality review is not the verdict but the structured conversation it forces among developers and leadership; the team already knows the problems.conf: high
explicitConferences and fagmiljø are formative substrate for engineers — single encounters (a lunch at Roots Bergen with Cockburn and Fowler) can determine a whole career.conf: high
explicitJuniors should learn IT architecture and core principles (TDD, design heuristics) before relying on language models — 'drive a Toyota Corolla before the Formula 1 car'.conf: high
explicitcorroboratedDevelopers will not be made unemployed by AI because only about 20% of system development is actually programming; the other 80% (understanding, coordinating, deciding) remains human.conf: medium
supports ←Podcast: Formal Methods for Every Engineer in an AI-Powered Future · p19 — Supports the claim that only ~20% of development is programming while the other 80% (understanding, deciding) remains human — Moreira's version is that defining correctness and understanding the system stay human even as AI writes the code.
explicitCheaper software production will expand the market for bespoke software — the frisørkjede that today tolerates a crappy booking system will commission a perfect one.conf: medium
explicitdevelopedQuality bars should differ by software 'mode' — high-stakes, regulated, long-lived public systems (sykepenger, straffesak) warrant rigorous engineering; throwaway personal apps warrant near-zero ceremony.conf: high
refines ←Bliki: Vibe Coding · p12 — Fowler turns Torrissen's discrete quality modes into continuous scaling dimensions: risk grows with code lifetime, audience size, and data sensitivity, not with code volume.
explicitProduct development culture systematically goldplates first iterations because tight user feedback over-identifies teams with a narrow user group.conf: medium
explicitThe Norwegian KS process under-serves software because it locks in quantifiable goals too early; in NAV-scale work, four-five years of learning makes the original goals obsolete.conf: high
implicitEngaging from inside imperfect institutional processes (KS) is more leveraged than refusing them, even though one risks being identified with their failures.conf: high
explicitSoftware is best understood as a learning activity — both technologically and domain-wise — and the bransje's appeal is that you never do the same thing twice.conf: high
implicitSaying yes by default — having '100 words for yes and none for no' — is an underrated career-building strategy in fagmiljø work.conf: medium
explicitThe cost structure of software is shifting further toward maintenance: if making code becomes near-free, the share of total cost that is keeping-it-running grows.conf: high

Arguments

Engineering practices matter more under AI, not less. strength: high

Explicit premises:

Teams with good practices get a steep productivity step-up from AI (TET/Claude observation).
Teams without good practices amplify existing chaos with AI.
AI forces tacit design knowledge to become explicit and written.
Long-lived systems still need maintainable code over decades.

Implicit premises:

Productivity gains under AI distribute unequally across teams; this distribution is determined by pre-existing practice quality.
Tacit design intuition does not transfer to LLMs; explicit articulation does.
The composition of a 30-year-old codebase is determined more by its early discipline than by its tooling at any moment.
An engineering leader's job is to set the discipline floor that determines whether AI is leverage or amplification of dysfunction.

Inferences:

Investing in engineering practices is a higher-leverage decision in 2026 than in 2020, even though it looks the same on paper.
Organisations that adopted AI coding without underlying practice discipline are sitting on technical debt that will be expensive to reverse.

Microservices should be 'an architecture of last resort'; default to monolithic in-process designs. strength: medium

Explicit premises:

Distribution adds complexity that often outweighs the local-simplicity gains.
Empirical studies suggest all-in-one-class is best up to ~500 lines; only then do you need additional structure.
Vlad Khononov / Balancing Coupling shows local-vs-global complexity tradeoff is the right lens.
Teams adopt microservices for fashion rather than for goals that justify the cost.

Implicit premises:

Global complexity is harder to perceive than local complexity; therefore biases push teams toward microservices.
Most domains do not change fast enough to need distributed flexibility (forvaltningsloven changes rarely).
Architecture choices should be derivable from domain volatility, not from team-size or hiring fashion.

Inferences:

If you cannot articulate the global-complexity cost of your microservice topology, you have not yet earned it.
Many existing microservice systems would deliver better value as well-modularised monoliths.

Code-quality reviews should not produce verdicts but facilitate adult education for leadership. strength: high

Explicit premises:

Developers already know the problems; the review surfaces them officially.
Traffic-light verdicts are over-simplified for the real tradeoffs.
Bad choices are usually due to prioritisation pressure, not incompetence or unwillingness.
Leadership lacks the technical context to interpret detailed findings without translation.

Implicit premises:

The bottleneck on improvement is leadership understanding, not developer knowledge.
External authority can grant developers permission to surface concerns they already had.
Translating between technical and leadership levels is a distinct skill worth charging consulting rates for.

Inferences:

An organization that pays for a code-quality review and gets a verdict has been short-changed.
If your consultants will not be tabloid with leadership, you are not getting value from them.

Junior developers should learn fundamentals before leaning on AI tooling. strength: high

Explicit premises:

TDD, software design principles, and architecture are still load-bearing 20 years on.
Driving a 'Formula 1' (language model) without a Toyota Corolla (fundamentals) is risky.
AI tools demand explicit articulation of design — which juniors cannot do without the fundamentals.

Implicit premises:

Without internalised principles, a junior cannot recognise when AI output is wrong.
The ability to drive a language model well is bounded above by your own design vocabulary.
Communities like JavaZone, Booster, Kodemaker fagdag are still the cheapest way to acquire the vocabulary.

Inferences:

Organisations that hire juniors and route them through AI-first workflows are creating a generation that cannot diagnose bad output.
The seniors who can review AI work will be in higher demand, not lower.

Software jobs will not disappear despite AI generation. strength: medium

Explicit premises:

Only ~20% of system development is programming.
Cheaper software grows the market (long-tail bespoke).
Maintenance share of total cost grows as creation cost falls.
High-stakes systems still require human accountability.

Implicit premises:

The 80% of non-programming work is harder to automate than programming itself.
Demand for software is highly elastic with respect to price.
Accountability cannot be transferred to a model.

Inferences:

The professional category may bifurcate: low-stakes vibecoders for throwaway apps; engineering-discipline professionals for regulated long-lived systems.
Engineering leadership becomes more, not less, distinctive as a role.

JavaZone's deep success is not its peak attendance but its generational continuity. strength: medium

Explicit premises:

Many founder-driven conferences die when founders move on.
JavaZone is now on roughly the sixth generation of program committees.
The hardest organisational act was getting someone else to take over.

Implicit premises:

Community institutions require explicit succession mechanisms.
Founders should plan for their own removal as part of building.
Conference longevity is a proxy for the health of a craft community.

Inferences:

Other Norwegian fagmiljø institutions (JavaBin, Dataforeningen, Booster) should be evaluated on succession not on current attendance.

Narratives

Roots Bergen (Recent Object Oriented Trends conference, early 2000s): Torrissen as a young developer has lunch with Alistair Cockburn and Martin Fowler, decides this is what he wants to do, joins the early JavaBin programkomite — eventually becoming program committee lead for JavaZone's first 5-6 years.
→ Implicitly supports the proposition that single conference encounters can be career-defining and the broader claim that fagmiljø is formative substrate.
The VAT war story: JavaBin volunteer organisers, as 'pur unge utviklere', personally on the hook when Skatteetaten claimed VAT was due on conference tickets; Sun Microsystems bailed them out.
→ Texture for the amateur-volunteer origin of Norwegian Java community; supports the implicit point that institutions get built by people who don't know they're not allowed to do this.
First NAV Sykepenger workshop: developers were surprised the reviewers didn't show up in suits with tape recorders. Torrissen reframes review as 'å sitte rundt et bord og snakke om faget vårt'.
→ Implicitly supports the proposition that the review's value is process, not verdict.
His son, freshly out of military service, vibecoding apps from home one per day, hoping ad revenue will arrive; 'arveløs så mange ganger at det funker ikke mer'.
→ Personifies camp 3 of the AI-coding taxonomy and the throwaway-app long tail; defines 'vibecoding' by example.
Sykepenger architecture: from coordinated to choreographed event-driven design where each step does not know where it sits in the flow — but forvaltningsloven is stable, so the flexibility may not be needed; loose coupling justified instead by drift/resilience.
→ Concrete example of architecture chosen for legitimate but secondary reasons rather than for fashion; supports the claim that reflection on domain volatility should drive design.
December obsession with Advent of Code at Novit/Kold (Kotlin), spending hours not on solving but on making the solution beautiful.
→ Personal acknowledgement that aesthetic craft attachment is real, even as he argues it matters less now — gives the concession emotional weight.
Talk at Kode24-dagen the day before recording: a TDD talk that ran half an hour past, on a practice from 2004 still being explained in 2026.
→ Supports the claim that fundamentals are durable across two decades.
TET/Telenor's Claude adoption talk: teams with mature engineering practices saw productivity step-ups; teams without saw it fall.
→ Empirical anchor for the engineering-practices-matter-more argument.
KOS (millions of lines, pre-distribution): unmaintainable monolith at Norge Tilsynsmyndigheter / Nord. Audun and Torrissen both worked there.
→ Counter-narrative to Torrissen's monolith preference; supports Audun's social-scaling argument for microservices.
Frisørkjede that today uses a crappy generic booking system, but in a world of cheap bespoke software would commission a perfect one.
→ Hypothetical illustration of demand-elasticity / long-tail bespoke argument.

Questions addressed

✅ What does 'good code quality' mean in 2026?
Obvious over clever; readable and maintainable by a varied team over decades; fit for the system's mode rather than measured by static metrics.
✅ How should engineering practice change in the AI era?
Double down on engineering discipline — fast feedback, observability, frequent delivery, explicit design, ADRs. AI raises the marginal value of these, doesn't replace them.
✅ Will developers be unemployed?
No: programming is ~20% of the work; the market for bespoke software expands; high-stakes work still requires human accountability.
⭕ When are microservices justified?
Disagreement: Torrissen says rarely (last resort); Audun says regularly for social scaling because in-process boundaries don't hold. The conversation names but does not resolve this.
✅ What should juniors do?
Learn fundamentals (architecture, TDD, core principles) before relying on LLMs; engage with fagmiljø.
✅ What is the value of an external code-quality review?
Not a verdict but a facilitated conversation that re-surfaces what developers already know, and translates it for leadership.
⭕ How should the Norwegian KS process serve software better?
Critique articulated (over-quantification, lock-in to obsolete goals) but reform path is unspecified beyond 'focus more on how to work than on what to achieve'.
⭕ What survives of aesthetic craft when machines write the code?
Personal mourning acknowledged; 'beautiful code' likely fades as a professional value but the conversation does not work out what should replace aesthetic discipline as a craft anchor.
⭕ When the code-quality review is itself agentic, what happens?
Joked about. Not engaged.

Gaps

incompleteTorrissen's frame is largely Norwegian consultancy and public-sector. The 30-year-lifespan argument is anchored in NAV/Skatt/politi; he gestures at differential quality bars for low-stakes consumer apps but does not engage with product-company contexts (startup, scaleup, SaaS) where the relevant time horizon is 3-5 years and the relevant readers are 5-10 engineers, not 70 forvaltere.
Read next: Read this against the Pocock workshop extraction (product-company AI workflow) and Vidar Moe (Heis), to see how product-company engineers calibrate quality differently.
incompleteThe microservices disagreement with Audun is left as a clean disagreement; the conversation doesn't work out under what conditions Torrissen's 'last resort' would tip to Audun's 'social scaling necessity'. A reader is left without a heuristic to decide.
Read next: Vlad Khononov's 'Balancing Coupling' (cited by Torrissen); Audun's reference to KOS as evidence; James Lewis / Sam Newman on microservices boundaries; possibly recent Fowler/Bockeler 'static sensors' work that already sits in the corpus.
closed byArticle: Modular Edge Computing at Multi-Tenant SaaS Scale on Cloudflare Workers — Supplies the missing tipping-point heuristic for when Torrissen's 'microservices as last resort' flips to Audun's 'social-scaling necessity': the split stops being a last resort exactly when (a) a single shared execution unit's blast radius spans an unacceptable number of tenants/teams, and (b) the platform offers a same-process call primitive (Cloudflare service bindings) that removes the network-hop cost — absent (b), the coupling cost of splitting still favors keeping the monolith.
incompleteThe 'engineering practices matter more under AI' claim rests on one cited Telenor talk. Strong intuition, weak evidence. A serious version needs DORA-style measurement of practice maturity × AI uplift.
Read next: DORA 2025 (already in user's library); the Entur AI adoption piece; Addy Osmani's agent patterns; any rigorous productivity studies.
incompleteThree-camp taxonomy of AI-coders is clean but binary on camp 3 (vibecoders) — conflates throwaway-app-spammers with large-scale parallel-agentic professional work. These have opposite stakes and opposite engineering risks.
Read next: Gene Kim's vibecoding series; Steve Yegge's manifesto; Anthropic harness-design talk (already in extractions); 'No Vibes Allowed' counter-pieces.
closed byBliki: Vibe Coding — Provides the distinction Torrissen's camp-3 taxonomy conflates: vibe coding (never looking at the code, appropriate only for disposable software) is categorically different from professional agentic programming (p1, p2, p5).
incompleteThe 'obvious over clever' principle is presented as inheritance from NAV's tekniske retning but the tradeoff against domain-modelling power, type-system expressiveness, and idiomatic language use is not explored. A 'maximally obvious' codebase in a functional language with strong types may look obscure to a Java-trained 70-forvalter pool.
Read next: Greg Young / Vlad Khononov on domain modelling; Ousterhout's 'A Philosophy of Software Design'; Rich Hickey's 'Simple Made Easy' (vs. 'easy ≠ obvious').
incompleteTorrissen acknowledges he's about to participate in a recursive case (reviewing code that was itself generated agentically) and only jokes. The methodology gap — how does code review change when the developer's intent is partially encoded in prompts, ADRs, and context files rather than commit history — is left for next time.
Read next: Anthropic 'harness design' talk and the Pocock workshop already in this corpus.
incompleteThe advice to juniors assumes the fundamentals taught today are the right ones; doesn't engage with the possibility that fundamentals themselves need re-curation for a world where LLMs are the second author. What does TDD even mean when test generation is also automated?
Read next: Kent Beck's recent 'Tidy First?' work on AI and design; 'starving genies' series; DORA on AI testing practices.
uninformedTorrissen disclaims familiarity with the formal 'distribution law' he invokes (Parnas/Helland-style). He gets the spirit right but doesn't engage with the literature on when distribution is forced (latency, regulatory, fault isolation).
Read next: Pat Helland's papers; Parnas on module boundaries; Vlad Khononov directly.
incompleteCode quality discussion is silent on data and persistence design — arguably the longest-lived and hardest-to-change layer in 30-year systems. The whole conversation is about behavioural code.
Read next: Stripe-style schema evolution practice; Martin Kleppmann's data engineering work; event-sourcing reflections from CQRS practitioners.

Closes gaps elsewhere

Eight years of wanting, three months of building with AI · g2 — Torrissen answers how juniors should calibrate AI use: learn IT architecture and core principles (TDD, design heuristics) before relying on language models — drive the Toyota Corolla before the Formula 1 car.

13) Tobias K. Torrissen om kodekvalitet, konferanser og AI

Structure

Key terms

Propositions

Arguments

Narratives

Questions addressed

Gaps

Closes gaps elsewhere

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